# Working with items on sheets in Amazon Quick Sight analyses Working with items on sheets Use this section to learn how to work with visuals and other items as you author sheets in Quick Sight **Topics** + [ # Adding visuals to Quick Sight analyses ](creating-a-visual.md) + [ # Using Topics on sheets in Amazon Quick Sight ](using-q-topics-on-sheets.md) + [ # Visual types in Amazon Quick Sight ](working-with-visual-types.md) + [ # Formatting in Amazon Quick ](formatting-a-visual.md) + [ # Customizing data presentation ](analyzing-data-analyses.md) # Adding visuals to Quick Sight analyses Adding visuals A *visual* is a graphical representation of your data. You can create a wide variety of visuals in an analysis, using different datasets and visual types. After you have created a visual, you can modify it in a range of ways to customize it to your needs. Possible customizations include changing what fields map to visual elements, changing the visual type, sorting visual data, or applying a filter. Quick Sight supports up to 50 datasets in a single analysis, and up to 50 visuals in a single sheet, and a limit of 20 sheets per analysis. You can create a visual in several ways. You can select the fields that you want and use AutoGraph to let Amazon Quick Sight determine the most appropriate visual type. Or you can choose a specific visual type and choose fields to populate it. If you aren't sure what questions your data can answer for you, you can choose **Suggested** on the tool bar and choose a visual that Amazon Quick Sight suggests. Suggested visuals are ones that we think are of interest, based on a preliminary examination of your data. For more information about AutoGraph, see [Using AutoGraph](autograph.md). You can add more visuals to the workspace by choosing **Add**, then **Add visual**. Visuals created after June 21, 2018, are smaller in size, fitting two on each row. You can resize the visuals and drag them to rearrange them. To create a useful visual, it helps to know what question you are trying to answer as specifically as possible. It also helps to use the smallest dataset that can answer that question. Doing so helps you create simpler visuals that are easier to analyze. ## Fields as dimensions and measures In the **Visuals** pane, dimension fields have blue icons and measure fields have orange icons. *Dimensions* are text or date fields that can be items, like products. Or they can be attributes that are related to measures and can be used to partition them, like sales date for sales figures. *Measures* are numeric values that you use for measurement, comparison, and aggregation. You typically use a combination of dimension and measure fields to produce a visual, for example sales totals (a measure) by sales date (a dimension). For more information about the types of fields expected by the different visual types, see the specific visual type topics in the [Visual types in Amazon Quick Sight](working-with-visual-types.md) section. For more information about changing a field's measure or dimension setting, see [Setting fields as a dimensions or measures](setting-dimension-or-measure.md). ## Field limitations You can only use one date field per visual. This limitation applies to all visual types. You can't use the same field for more than one dimension field well or drop target on a visual. For more information about how expected field type is indicated by field wells and drop targets, see [Using visual field controls](using-visual-field-controls.md). ## Searching for fields If you have a long field list in the **Fields list** pane, you can search to locate a specific field. To do so, choose the search icon at the top of the **Data** pane and then enter a search term into the search box. Any field whose name contains the search term is shown. Search is case-insensitive and wildcards aren't supported. Choose the cancel icon (**X**) to the right of the search box to return to viewing all fields. ## Adding a visual Use the following procedure to create a new visual. **To create a new visual** 1. Open the [Quick console](https://quicksight.aws.amazon.com/). 1. On the Quick homepage, choose the analysis that you want to add a visual to. 1. On the analysis page, choose the dataset that you want to use from the dataset list at the top of the **Data** pane. For more information, see [Adding a dataset to an analysis](adding-a-data-set-to-an-analysis.md). 1. Open the **Visualize** pane, choose **Add**, and then choose **Add visual**. A new, blank visual is created and receives focus. 1. Use one of the following options: + Choose the fields to use from the **Data** pane at left. If the fields aren't visible, choose **Visualize** to display it. Amazon Quick Sight creates the visual, using the visual type it determines is most compatible with the data you selected. + Choose the dropdown arrow next to the **ADD** button to choose a visual type. After the visual is created, choose the fields that you want to populate it. 1. Choose the icon of a visual type from the **Visual types** pane. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/visual-types.png) The field wells display the fields that are visualized. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/field-wells.png) 1. From the **Data** pane, drag the fields that you want to use to the appropriate field wells. Typically, you want to use dimension or measure fields as indicated by the color of the target field well. If you choose to use a dimension field to populate a **Value** field well, the **Count** aggregate function is automatically applied to it to create a numeric value. Amazon Quick Sight creates the visual using the visual type you selected. + Create a visual using a suggestion. On the tool bar, choose **Suggested**, then choose a suggested visual. # Importing Amazon Quick Sight visuals to an analysis Importing visuals Quick Sight authors can import Quick Sight visuals from one analysis or dashboard to a new analysis that has access privileges. When you import a visual from a Quick Sight analysis or dashboard to another Quick Sight analysis, the following dependencies are imported along with the visual. + Datasets associated with the visual + All parameters that are configured to the visual + Calculated fields that are configured to the visual + Filter definitions + Visual properties + Conditional formatting rules Use the following sections to learn more about importing Quick Sight visuals. **Topics** + [ ## Considerations ](#import-visuals-considerations) + [ ## Import a visual ](#import-visual-procedure) ## Considerations Before you import a visual, review the following limitations. + The Quick Sight author that wants to import a visual must have ownership privileges to the analysis that they want to import the visual to + Filter controls can't be imported + Importing visuals from multiple sheets at a time is not supported + Some user configurations including filter configurations that are maintained against bookmarks and alerts are not supported ## Import a visual Use the following procedure to import a visual from a source dashboard or analysis to a different analysis. 1. Open the [Quick console](https://quicksight.aws.amazon.com/). 1. Open the analysis that you want to import a visual to. 1. Choose **File**, and then choose **Import**. Alternatively, you can choose the **Import** icon in the **ADD** toolbar. 1. The **Asset explorer** modal opens. A list of all eligible source analyses and dashboards that you can access are displayed. Choose the artifact that you want to import a visual from, and then choose **LOAD**. Alternatively, enter the name of the source artifact that contains the visual that you want to import in the **Find source to insert** search bar. Choose the artifact that you want, and then choose **LOAD**. 1. In the **Select visuals to import** page that opens, choose the sheet that contains the visuals that you want to import, and then choose the visuals that you want to import. You can only import visuals from one sheet at a time. When you have chosen all visuals that you want to import, choose **IMPORT**. After a successful import job, the imported visuals are added to the destination analysis. The imported visuals retain the original properties that were configured to them in the source dashboard or analysis. Imported visuals inherit the theme-level properties from the theme that is applied to the destination analysis. # Duplicating Quick Sight visuals Duplicating visuals You can duplicate a visual to make a new copy of it on the same sheet or on a different sheet. To duplicate a visual, on the **v**-shaped on-visual menu, choose **Duplicate visual to**, then choose the sheet where you want the visual to appear. The display automatically shows you the duplicated visual. Duplicated visuals keep all the same filters and settings as the source visual. However, if you duplicate a visual onto a different sheet, all of its copied filters apply to the duplicate only. All copied filters are scoped down to apply only to that visual. If you want the filters to apply to more visuals on the new sheet, edit the filter and change the setting. Parameters and controls apply to all sheets. To make parameter controls work with a visual that you duplicate to a different sheet, add filters on the target sheet and connect them to the parameter. To do this, choose **Custom filter** as the filter type. # Renaming Amazon Quick Sight visuals Renaming visuals Use the following procedure to rename a visual. **To rename a visual** 1. On the analysis page, choose the visual that you want to rename. 1. Select the visual name at the top left of the visual and enter a new name. 1. Press **Enter** or click outside of the visual name field to save the new name. # Viewing visual data in Amazon Quick Sight Viewing visual data Amazon Quick Sight offers a variety of ways to see the details of the data being displayed in a visual. The axes or rows and columns of the visual (depending on the visual type) have labels. Hovering over any graphical element in a visual displays the data associated with that element. Some visual types use visual cues to emphasize the element that you are hovering over and make it easier to differentiate. For example, the visual type might change the color of the element or highlight it. Use the following sections to learn more about viewing data in visuals. **Topics** + [ # Viewing visual details ](viewing-visual-details.md) + [ # Scrolling through visual data ](scrolling-through-visual-data.md) + [ # Focusing on visual elements ](focusing-on-visual-elements.md) + [ # Excluding visual elements ](excluding-visual-elements.md) + [ # Searching for specific values in your data in Quick Sight ](search-filter.md) # Viewing visual details When viewing a visual, you can hover your cursor over any graphical element to get details on that element. For example, when you hover over a single bar on a bar chart, information about that specific bar displays in a tooltip. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/bar-detail.png) Hovering your cursor over a single data point on a scatter plot also displays information about that specific data point. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/scatter-plot-detail.png) You can customize the information that appears when you hover your cursor over data in a chart. For more information, see [Tooltips](customizing-visual-tooltips.md). # Scrolling through visual data For bar charts, line charts, and pivot tables, the content of the visual can be larger than the size that you want the visual to be. In these cases, scrub bars appear so you can either reduce the data that is displayed or scrub through it. This process is similar to the way that you can scrub through a video. To reduce the length of the scrub bar, hover over one end of it until the cursor changes shape. Then drag the widget to make the scrub bar larger or smaller. To scroll through the data, click and hold the scrub bar and slide it toward the end that you want to see. # Focusing on visual elements When viewing visuals, you can choose data that you want to focus on or exclude. To perform this choice, choose an element such as a bar or bubble, or a row or column header. Focusing on or excluding data causes Quick Sight to create a filter and show only the data that you selected. To remove the filter, choose **Filters** at left and then disable or delete the filter. You can also use **Undo** to remove a filter. If your visual has a legend that shows categories (dimensions), you can click on the values in the legend to see a menu of available actions. For example, suppose that your bar chart has a field in the **Color** or **Group/Color** field well. The bar chart menu displays the actions that you can choose by clicking or right-clicking on a bar, such as the following: + Focusing on, or excluding, visual elements + Changing colors of visual elements + Drilling down into a hierarchy + Custom actions activated from the menu, including filtering or URL actions # Excluding visual elements When viewing visuals, you can choose an element on the visual, and then choose to focus on the element. Elements to focus on can include, for example, a bar or bubble, or a row or column header in the case of a pivot table. The exception is that you can't exclude elements that are mapped to date fields. You can exclude multiple elements on a single chart. Excluding the element creates a filter that removes only that element from the visual. To see the excluded element again, you can either choose **Undo** on the application bar, or you can disable or delete the filter. For more information about filters, see [Filtering data in Amazon Quick Sight](adding-a-filter.md). # Searching for specific values in your data in Quick Sight Searching for specific values When filtering your visual data, previewing anomalies, or using list or dropdown controls in a dashboard, you can quickly search for values that interest you. You can search for specific values or all values that contain a specific search query. For example, searching for *al* in a list of U.S. states returns **Al**abama, **Al**aska, and C**al**ifornia. You can also use wildcard search to search for all values that match a specific character pattern. For example, you can search for all U.S. states that end with the letters *ia* and narrow the results down to California, Georgia, Pennsylvania, Virginia, and West Virginia. **To search for values in a filter or control**, enter a search query in the search bar. ## Using wildcard search The following wildcard characters can be used to find values in Quick Sight filters, list and dropdown controls, and anomaly previews. + **\$1** - Use an asterisk symbol to search for values that match zero to many characters in a specific position. + **?** - Use a question mark to match a single character in a specific position. + **\$1** - Use a backslash to escape the **\$1**, **?**, or **\$1** wildcard characters and search for them in your query. For example, you can search for phrases that end with a question mark. Following are examples of how supported wildcard characters can be used in a Quick Sight search query. + **al** - This query searches for all values with **al** and returns Alabama, Alaska, and California. + **al\$1** - This query searches for all values that begin with **al** and end with zero to multiple characters. It returns Alabama, and Alaska in a list of U.S. states. + **\$1ia** - This query searches for all values that begin with zero to multiple characters and end with letters **ia**. It returns California, Georgia, Pennsylvania, Virginia, and West Virginia. + **\$1al\$1** - This query searches for all values with zero to multiple characters before and after the letters **al**. It returns Alabama, Alaska, and California. + **a?a?a?a** - This query searches for all values with a single character in the exact positions between the **a** letters. It returns Alabama. + **a?a\$1a** - This query searches for all values with a single character between the first two **a** letters and multiple characters between the second two **a** letters. It returns Alabama and Alaska. + **How\$1\$1?** - This query searches for values that begin with **How**, followed by zero to multiple characters, and end with a question mark. The backslash (\$1) in this query informs Quick Sight to search for question marks in each value, rather than use the question mark symbol as a wildcard character. This query returns the questions, How are you? and, How is this possible? + **\$1\$1\$1** - This query searches for values that begin with an asterisk and are followed by zero to multiple characters. The backslash (\$1) in this query informs Quick Sight to search for an actual asterisk in the values, rather than use the asterisk symbol as a wildcard character. This query returns values such as \$1all, \$1above, and \$1below. + **\$1\$1\$1** - This query searches for values with a backslash, followed by zero to multiple characters. The first backslash (\$1) in this query informs Quick Sight to search for the second backslash (\$1) in each value, rather than use the backslash symbol as a wildcard character. This query returns results such as \$1Home. + **???** - This query searches for values that contain three characters. It returns values such as ant, bug, and car. # Exporting data from visuals **Note** Export files can directly return information from the dataset import. This makes the files vulnerable to CSV injection if the imported data contains formulas or commands. For this reason, export files can prompt security warnings. To avoid malicious activity, turn off links and macros when reading exported files. Using the Amazon Quick console, you can export data from any type of chart or graph. The export contains only the data in the fields that are currently visible in the selected visualization. Any data that is filtered out is excluded from the export file. You can export data into the following formats: + A text file containing comma-separated values (CSV), available for all visual types. + A Microsoft Excel workbook file (.xslx), available for pivot tables and table charts only. The following rules apply: + Exported files are downloaded to the default download directory configured in the browser that you're currently using. + The downloaded file is named for the visualization that you exported it from. To make the file name unique, it has a sequential timestamp (a Unix epoch data type). + Default limit for export to CSV format: 500 MB or 1M rows whichever comes first + Default limit for export to Excel format: + from Pivot Table visual 400K cells or 50K rows + from Table visual 800K cells or 100K rows **Note** With a subscription to Paginated Reporting, you are able to [schedule the export of visuals in CSV and Excel formats](https://docs.amazonaws.cn/quicksight/latest/user/sending-reports.html) and export up to 3M rows (CSV) and 16M cells (Excel). + You can't export data from an insight, because insights consume the data, but don't contain the data. + Quick Sight doesn't support exporting data from more than a single visualization at a time. To export data from additional visuals in the same analysis or dashboard, repeat this process for each visual. To export all the data from a dashboard or analysis, you need to connect to the original data source using valid credentials and a tool that you can use to extract data. Use the following procedure to export data from a visualization in Amazon Quick Sight. Before you begin, open the analysis or dashboard that contains the data that you want to export. **To export data from a visualization** 1. Choose the visualization that you want to export. Make sure that it is selected and highlighted. 1. At top right on the visual, open the menu and choose one of the following: + To export to CSV, choose **Export to CSV**. + To export to XSLX, choose **Export to Excel**. This option is available only for pivot tables and table charts. 1. Depending on your browser settings, one of the following happens: + The file automatically goes to your default **Download** location. + A dialog box appears so you can choose a file name and location. + A dialog box appears so you can choose to open the file with the default software or to save to. # Refreshing visuals in Quick Sight Refreshing visuals When you work in an Quick Sight analysis or dashboard, visuals refresh and reload when you change something that affects them, such as updating a parameter or filter control. If you switch to a new sheet after a parameter or filter changes, only the visuals affected by the change refresh on the new sheet. Otherwise, visuals update every 30 minutes when you switch sheets. This is the default behavior for all analyses and dashboards. If you want to refresh all visuals when you switch sheets, regardless of a change, you can do so for each analysis that you create. **To refresh all visuals each time that you switch sheets in an analysis** 1. In Amazon Quick, open the analysis. 1. In the analysis, choose **Edit > Analysis Settings**. 1. In the **Analysis Settings** pane that opens, for **Refresh Options**, toggle on **Reload visuals each time I switch sheets**. 1. Choose **Apply**. # Deleting Amazon Quick Sight visuals Deleting visuals Use the following procedure to delete a visual. **To delete a visual** 1. On the analysis page, choose the visual that you want to delete. 1. Choose the on-visual menu at the upper-right corner of the visual, and then choose **Delete**. # Using Topics on sheets in Amazon Quick Sight Using Topics Amazon Quick Sight provides a guided workflow for creating topics. You can step out of the guided workflow and come back to it later, without disrupting your work. By enabling one or more Quick Sight topics in your analysis workspace, you activate the ML-powered automated data prep , which speeds Natural Language (NL) topic creation. Automated data prep automatically selects high value fields, based on how they are used and on common Q&A needs. It automatically chooses user-friendly field names and synonyms, based on terms from existing analyses and on common dictionaries. It also automatically formats data, so it's immediately useful when presented. Automated data prep binds the topic to your analysis and prepares an index for searching in natural language. A blue dot denotes this binding. Dashboard users find that the new Amazon Quick Sight topic is automatically selected, making it easier for them to query the dataset. The following rules apply to working with topics: + You must be an owner of the underlying dataset before you can create a topic using that dataset or an analysis that uses that dataset. + You must be an owner of a topic before you can link the existing topic to an analysis. **To enable a topic** 1. Open the analysis that you want to use with automated data prep . 1. On the top navigation bar, choose the topic icon. 1. Choose one of the following: + To activate a new topic, select **Create new topic** and enter a topic title and optional description. + To activate an existing topic, select **Update existing topic** and choose the topic from the list. 1. Choose **ENABLE TOPIC** to confirm your choice. 1. When the topic is finished processing, you can use what it learned from the analysis to ask questions in natural language. Now, when users navigate to the dashboard, the linked topic is automatically selected in the search bar. After a topic is linked to an analysis, further updates to the analysis are not automatically synced to the topic. Authors need to manage updating topics manually from the **Topics** page. When you enable a topic for an analysis or dashboard, you are starting a process where automated data prep learns from how you analyze your data. Ask it questions, and provide feedback and further information by following the screen prompts. The more you interact with the topic, the better prepared it becomes to answer your questions. To learn more, see [https://docs.amazonaws.cn/quicksight/latest/user/quicksight-q-starting-from-sheets.html](https://docs.amazonaws.cn/quicksight/latest/user/quicksight-q-starting-from-sheets.html). # Visual types in Amazon Quick Sight Visual types Amazon Quick Sight offers a range of visual types that you can use to display your data. Use the topics in this section to learn more about the capabilities of each visual type. **Topics** + [ ## Measures and dimensions ](#measures-and-dimensions) + [ ## Display limits ](#display-limits) + [ ## Hiding or displaying the other category ](#other-category) + [ ## Customizing the number of data points to display ](#customizing-number-of-data-points) + [ # Using AutoGraph ](autograph.md) + [ # Using bar charts ](bar-charts.md) + [ # Using box plots ](box-plots.md) + [ # Using combo charts ](combo-charts.md) + [ # Using custom visual content ](custom-visual-content.md) + [ # Using donut charts ](donut-chart.md) + [ # Using funnel charts ](funnel-charts.md) + [ # Using gauge charts ](gauge-chart.md) + [ # Using heat maps ](heat-map.md) + [ # Using Highcharts ](highchart.md) + [ # Using histograms ](histogram-charts.md) + [ # Using image components ](image-component.md) + [ # Using KPIs ](kpi.md) + [ # Using layer maps ](layered-maps.md) + [ # Using line charts ](line-charts.md) + [ # Creating maps and geospatial charts ](geospatial-charts.md) + [ # Using small multiples ](small-multiples.md) + [ # Using pie charts ](pie-chart.md) + [ # Using pivot tables ](pivot-table.md) + [ # Using radar charts ](radar-chart.md) + [ # Using Sankey diagrams ](sankey-diagram.md) + [ # Using scatter plots ](scatter-plot.md) + [ # Using tables as visuals ](tabular.md) + [ # Using text boxes ](textbox.md) + [ # Using tree maps ](tree-map.md) + [ # Using waterfall charts ](waterfall-chart.md) + [ # Using word clouds ](word-cloud.md) ## Measures and dimensions We use the term *measure* to refer to numeric values that you use for measurement, comparison, and aggregation in visuals. A measure can be either a numeric field, like product cost, or a numeric aggregate on a field of any data type, like count of transaction IDs. We use the term *dimension* or *category* to refer to text or date fields that can be items, like products, or attributes that are related to measures and can be used to partition them. Examples are sales date for sales figures or product manufacturer for customer satisfaction numbers. Amazon Quick Sight automatically identifies a field as a measure or a dimension based on its data type. Numeric fields can act as dimensions, for example ZIP codes and most ID numbers. It's helpful to give such fields a string data type during data preparation. This way, Amazon Quick Sight understands that they are to be treated as dimensions and are not useful for performing mathematical calculations. You can change whether a field is displayed as a dimension or measure on an analysis-by-analysis basis instead. For more information, see [Fields as dimensions and measures](creating-a-visual.md#dimensions-and-measures). ## Display limits All visual types limit the number of data points they display, so that the visual elements (like lines, bars, or bubbles) are still easy to view and analyze. The visual selects the first *n* number of rows for display up to the limit for that visual type. The selection is either according to sort order, if one has been applied, or in default order otherwise. The number of data points supported varies by visual type. To learn more about display limits for a particular visual type, see the topic for that type. The visual title identifies the number of data points displayed if you have reached the display limit for that visual type. If you have a large dataset and want to avoid running into the visual display limit, use one or more filters to reduce the amount of data displayed. For more information about using filters with visuals, see [Filtering data in Amazon Quick Sight](adding-a-filter.md). For dashboards and analyses, Amazon Quick Sight supports the following: + 50 datasets per dashboard + 20 sheets per dashboard + 30 visualization objects per sheet **Note** Amazon Quick Sight supports over 30 different *visual types* (categories of charts and visualizations such as bar charts, pie charts, and line charts). Each analysis sheet can contain up to 30 *visual instances* (individual chart objects) of any combination of types. You can also choose to limit how many data points you want to display in your visual, before they are added to the **other** category. This category contains the aggregated data for all the data beyond the cutoff limit for the visual type you are using—either the one you impose, or the one based on display limits. You can use the on-visual menu to choose whether to display the **other** category. The **other** category doesn't show on scatter plots, heat maps, maps, tables (tabular reports), or key performance indicators (KPIs). It also doesn't show on line charts when the x-axis is a date. Drilling down into the **other** category is not supported. ## Hiding or displaying the other category Use the following procedure to hide or display the "other" category. **To hide or display the "other" category** 1. On the analysis page, choose the visual that you want to modify. 1. Choose the on-visual menu at the upper-right corner of the visual, and then choose **Hide "other" category** or **Show "other" category**, as appropriate. ## Customizing the number of data points to display You can choose the number of data points to display on the main axis of some visuals. After this number is displayed in the chart, any additional data points are included in the "other" category. For example, if you choose to include 10 data points out of 200, 10 display in the chart and 190 become part of the "other" category. To find this setting, choose the **v**-shaped on-visual menu, then choose **Format visual**. You can use the following table to determine which field well contains the data point setting and what number of data points the visual type displays by default. | Visual type | Where to find the data point setting | Default number of data points | | --- | --- | --- | | Bar chart, horizontal | **Y-axis** – **Number of data points displayed** | 10,000 | | Bar chart, vertical | **X-axis** – **Number of data points displayed** | 10,000 | | Combo chart | **X-axis** – **Number of data points displayed** | 2,500 | | Heat map | **Rows** – **Number of rows displayed** **Columns** – **Number of columns displayed** | 100 | | Line chart | **X-axis** – **Number of data points displayed** | 10,000 | | Pie chart | **Group/Color** – **Number of slices displayed** | 20 | | Tree map | **Group by** – **Number of squares displayed** | 100 | # Using AutoGraph AutoGraph isn't a visual type itself, but instead lets you tell Amazon Quick to choose the visual type for you. When you create a visual by choosing AutoGraph and then selecting fields, Amazon Quick uses the most appropriate visual type for the number and data types of the fields you select. ## Creating a visual using AutoGraph Use the following procedure to create a visual using AutoGraph. **To create a visual using AutoGraph** 1. On the analysis page, choose **Visualize** on the tool bar. 1. Choose **Add** on the application bar, and then choose **Add visual**. 1. On the **Visual types** pane, choose the AutoGraph icon. 1. On the **Fields list** pane, choose the fields that you want to use. # Using bar charts Amazon Quick supports the following types of bar charts, with either horizontal or vertical orientation: + **Single-measure** – A *single-measure bar chart* shows values for a single measure for a dimension. + **Multi-measure** – A *multi-measure bar chart* shows values for multiple measure for a dimension. + **Clustered** – A *clustered bar chart* shows values for a single measure for a dimension, grouped by another dimension. + **Stacked** – A *stacked bar chart* is similar to a clustered bar chart in that it displays a measure for two dimensions. However, instead of clustering bars for each child dimension by the parent dimension, it displays one bar per parent dimension. It uses color blocks within the bars to show the relative values of each item in the child dimension. The color blocks reflect the value of each item in the child dimension relative to the total for the measure. A stacked bar chart uses a scale based on the maximum value for the selected measure. + **Stacked 100 percent** – A *stacked 100 percent bar chart* is similar to a stacked bar chart. However, in a stacked 100 percent bar chart, the color blocks reflect the percentage of each item in the child dimension, out of 100 percent. Bar charts show up to 10,000 data points on the axis for visuals that don't use group or color. For visuals that do use group or color, they show up to 50 data points on the axis and up to 50 data points for group or color. For more information about how Amazon Quick handles data that falls outside display limits, see [Display limits](working-with-visual-types.md#display-limits). ## Creating single-measure bar charts Single-measure bar charts Use the following procedure to create a single-measure bar chart. **To create a single-measure bar chart** 1. On the analysis page, choose **Visualize** on the toolbar at left. 1. On the application bar at upper left, choose **Add**, and then choose **Add visual**. 1. On the **Visual types** pane, choose the **Horizontal bar chart** or **Vertical bar chart** icon. 1. From the **Fields list** pane, drag a dimension to the **X-axis** or **Y-axis** field well. 1. From the **Fields list** pane, drag a measure to the **Value** field well. ## Creating multi-measure bar charts Multi-measure bar charts Use the following procedure to create a multi-measure bar chart. **To create a multi-measure bar chart** 1. On the analysis page, choose **Visualize** on the toolbar at left. 1. On the application bar at upper-left, choose **Add**, and then choose **Add visual**. 1. On the **Visual types** pane, choose the **Horizontal bar chart** or **Vertical bar chart** icon. 1. From the **Fields list** pane, drag a dimension to the **X-axis** or **Y-axis** field well. 1. From the **Fields list** pane, drag two or more measures to the **Value** field well. ## Creating clustered bar charts Clustered bar charts Use the following procedure to create a clustered bar chart. **To create a clustered bar chart** 1. On the analysis page, choose **Visualize** on the toolbar at left. 1. On the application bar at upper left, choose **Add**, and then choose **Add visual**. 1. On the **Visual types** pane, choose the **Horizontal bar chart** or **Vertical bar chart** icon. 1. From the **Fields list** pane, drag a dimension to the **X-axis** or **Y-axis** field well. 1. From the **Fields list** pane, drag a measure to the **Value** field well. 1. From the **Fields list** pane, drag a dimension to the **Group/Color** field well. ## Creating stacked bar charts Stacked bar charts Use the following procedure to create a stacked bar chart. **To create a stacked bar chart** 1. On the analysis page, choose **Visualize** on the toolbar at left. 1. On the application bar at upper-left, choose **Add**, and then choose **Add visual**. 1. On the **Visual types** pane, choose the **Horizontal stacked bar chart** or **Vertical stacked bar chart** icon. 1. From the **Fields list** pane, drag a dimension to the **X-axis** or **Y-axis** field well. 1. From the **Fields list** pane, drag a dimension to the **Group/Color** field well. 1. From the **Fields list** pane, drag a measure to the **Value** field well. 1. (Optional) Add data labels and show totals: 1. On the menu in the upper-right corner of the visual, choose the **Format visual** icon. 1. In the **Visual** pane, choose **Data labels**. 1. Toggle the switch to display data labels. Labels for each measure value appear in the chart and the option to show totals appears in the pane. 1. Check **Show totals**. Totals appear for each bar in the chart. ## Creating stacked 100 percent bar charts Stacked 100% bar charts Use the following procedure to create a stacked 100 percent bar chart. **To create a stacked 100 percent bar chart** 1. On the analysis page, choose **Visualize** on the toolbar at left. 1. On the application bar at upper-left, choose **Add**, and then choose **Add visual**. 1. On the **Visual types** pane, choose the **Horizontal stacked 100% bar chart** or **Vertical stacked 100% bar chart** icon. 1. From the **Fields list** pane, drag a dimension to the **X-axis** or **Y-axis** field well. 1. From the **Fields list** pane, drag two or more measures to the **Value** field well. ## Bar chart features To understand the features supported by bar charts, use the following table. **** | Feature | Supported? | Comments | For more information | | --- | --- | --- | --- | | Changing the legend display | Yes, with exceptions | Multi-measure and clustered bar charts display a legend, while single-measure horizontal bar charts don't. | [Legends on visual types in Quick](customizing-visual-legend.md) | | Changing the title display | Yes | | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Changing the axis range | Yes | | [Range and scale on visual types in Quick](changing-visual-scale-axis-range.md) | | Showing or hiding axis lines, grid lines, axis labels, and axis sort icons | Yes | | [Axes and grid lines on visual types in Quick](showing-hiding-axis-grid-tick.md) | | Changing the visual colors | Yes | | [Colors in visual types in Quick](changing-visual-colors.md) | | Focusing on or excluding elements | Yes, with exceptions | You can focus on or exclude any bar on the chart, except when you are using a date field as the dimension for the axis. In that case, you can only focus on a bar, not exclude it. | [Focusing on visual elements](focusing-on-visual-elements.md) [Excluding visual elements](excluding-visual-elements.md) | | Sorting | Yes | You can sort on the fields you choose for the axis and the values. | [Sorting visual data in Amazon Quick](sorting-visual-data.md) | | Performing field aggregation | Yes | You must apply aggregation to the field or fields you choose for the value, and can't apply aggregation to the fields you choose for the axis or group/ color. | [Changing field aggregation](changing-field-aggregation.md) | | Adding drill-downs | Yes | You can add drill-down levels to the axis and Group/Color field wells. | [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md) | | Showing data labels | Yes | | [Data labels on visual types in Quick](customizing-visual-data-labels.md) | | Showing stacked bar chart totals | Yes | Showing totals in a stacked bar chart is only available when you choose to show data labels. | [Stacked bar charts](#create-bar-chart-stacked) | # Using box plots *Box plots*, also known as box and whisker plots, display data pooled from multiple sources into one visual, helping you make data-driven decisions. Use a box plot to visualize how data is distributed across an axis or over time, for example flights delayed over a 7-day time period. Typically, a box plot details information in quarters: + **Minimum** – The lowest data point excluding outliers. + **Maximum** – The highest data point excluding outliers. + **Median** – The middle value of the dataset. + **First Quartile** – The middle value between the smallest number and the median of the dataset. The first quartile doesn't include the minimum or the median. + **Third Quartile** – The middle value between the largest number and the median of the dataset. The third quartile doesn't include the maximum or the median. *Outliers* are extreme data points that aren't included in the calculation of a box plot's key values. Because outliers are calculated separately, their data points don't appear immediately after a box plot is created. Box plots display up to 10,000 data points. If a dataset contains more than 10,000 data points, a warning appears at the upper-right corner of the visual. Box plots support up to five metrics and one group-by, but don't render if duplicate metrics are supplied. Box plots support some calculated fields, but not all. Any calculated field that uses a window function, for example `avgOver`, results in a SQL error. Box plot visuals aren't compatible with MySQL 5.3 and earlier. **To create a basic box plot visual** 1. Sign in to Amazon Quick at [https://quicksight.aws.amazon.com/](https://quicksight.aws.amazon.com/). 1. Open Quick and choose **Analyses** on the navigation pane at left. 1. Choose one of the following: + To create a new analysis, choose **New analysis** at upper right. For more information, see [Starting an analysis in Quick Sight](creating-an-analysis.md). + To use an existing analysis, choose the analyses that you want to edit. 1. Choose **Add**, **Add visual**. 1. At lower left, choose the box plot icon from **Visual types**. 1. On the **Fields list** pane, choose the fields that you want to use for the appropriate field wells. Box plots require at least one unique measure field. 1. (Optional) Add drill-down layers by dragging one or more additional fields to the **Group/Color** field well. For more information about adding drill-downs, see [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md). To understand the features supported by box plots, see [Analytics formatting per type in Quick](analytics-format-options.md). For customization options, see [Formatting in Amazon Quick](formatting-a-visual.md). # Using combo charts Using a combo chart, you can create one visualization that shows two different types of data, for example trends and categories. Combo charts are also known as line and column (bar) charts, because they combine a line chart with a bar chart. Bar charts are useful for comparing categories. Both bar charts and line charts are useful for displaying changes over time, although bar charts should show a greater difference between changes. Amazon Quick supports the following types of combo charts: + **Clustered bar combo charts** – display sets of single-color bars where each set represents a parent dimension and each bar represents a child dimension. Use this chart to make it easy to determine values for each bar. + **Stacked bar combo charts** – display multi-color bars where each bar represents a parent dimension and each color represents a child dimension. Use this chart to make it easy to see relationships between child dimensions within a parent dimension. This chart shows the total value for the parent dimension and how each child adds to the total value. To determine the value for each child dimension, the chart reader must compare the size of the color section to the data labels for that axis. Both types of combo chart require only one dimension on the **X axis**, but are usually more effective when also displaying at least one measure under **Lines**. Use a combo chart only if you want to show a relationship between the bars and the lines. A good rule of thumb is that if you need to explain how the two chart types relate, you should probably use two separate charts instead. Because each chart works differently, it can be helpful to understand the following points before you begin: + The data points in each series render on different scales. Combo charts use a scale based on the maximum value for the selected measure. + The distance between the numbers on the axis won't match between the lines and bars, even if you select the same scale for each chart type. + For clarity, try to use different units for the measure in each data series. The combo chart is like using two different types of visualization at the same time. Make sure that the data in the bars (or columns) directly relates to the data in the line or lines. This relationship is not technically enforced by the tool, so it's essential that you determine this relationship yourself. Without some relation between the lines and bars, the visual loses meaning. You can use the combo chart visual type to create a single-measure or single-line chart. A single-measure combo chart shows one measure for one dimension. To create a multi-measure chart, you can choose to add multiple lines, or multiple bars. A multi-measure bar chart shows two or more measures for one dimension. You can group the bars in clusters, or stack them. For the bars, use a dimension for the axis and a measure for the value. The dimension is typically a text field that is related to the measure in some way and can be used to segment it to see more detailed information. Each bar in the chart represents a measure value for an item in the dimension you chose. Bars and lines show up to 2,500 data points on the axis for visuals that don't use group or color. For visuals that do use group or color, bars show up to 50 data points on the axis and up to 50 data points for group or color, while lines show 200 data points on the axis and up to 25 data points for group or color. For more information about how Amazon Quick handles data that falls outside display limits, see [Display limits](working-with-visual-types.md#display-limits). ## Combo chart features To understand the features supported by combo charts, use the following table. **** | Feature | Supported? | Comments | For more information | | --- | --- | --- | --- | | Changing the legend display | Yes, with exceptions | Multi-measure combo charts display a legend, and single-measure combo charts don't. | [Legends on visual types in Quick](customizing-visual-legend.md) | | Changing the title display | Yes | | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Changing the axis range | Yes | You can set the range for the axis. | [Range and scale on visual types in Quick](changing-visual-scale-axis-range.md) | | Showing or hiding axis lines, grid lines, axis labels, and axis sort icons | Yes | | [Axes and grid lines on visual types in Quick](showing-hiding-axis-grid-tick.md) | | Changing the visual colors | Yes | | [Colors in visual types in Quick](changing-visual-colors.md) | | Focusing on or excluding elements | Yes, with exceptions | You can focus on or exclude any bar on the chart, except when you are using a date field as the dimension for the axis. In that case, you can only focus on a bar, not exclude it. | [Focusing on visual elements](focusing-on-visual-elements.md) [Excluding visual elements](excluding-visual-elements.md) | | Sorting | Yes | You can sort on the fields you choose for the axis and the values. | [Sorting visual data in Amazon Quick](sorting-visual-data.md) | | Performing field aggregation | Yes | You must apply aggregation to the field or fields you choose for the value. You can't apply aggregation to the fields you choose for the axis or group/color. | [Changing field aggregation](changing-field-aggregation.md) | | Adding drill-downs | Yes | You can add drill-down levels to the axis and Group/Color field wells. | [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md) | | Synchronizing y-axis | Yes | Synchronize the y-axes for both bars and lines into a single axis. | [Range and scale on visual types in Quick](changing-visual-scale-axis-range.md) | ## Creating a combo chart Use the following procedure to create a combo chart. **To create a combo chart** 1. On the analysis page, choose **Visualize** on the tool bar. 1. Choose **Add** on the application bar, and then choose **Add visual**. 1. On the **Visual types** pane, choose one of the combo chart icons. 1. From the **Fields list** pane, drag the fields that you want to use to the appropriate field wells. Typically, you want to use dimension or measure fields as indicated by the target field well. If you choose to use a dimension field as a measure, the **Count** aggregate function is automatically applied to it to create a numeric value. You can create combo charts as follows: + Choose a dimension for the **X axis**. + To create a single-measure combo chart, choose one measure for either **Bars** or **Lines**. + To create a multi-measure combo chart, choose two or more measures for the **Bars** or **Lines** field well. + Optionally, add a dimension to the **Group/Color** field well. If you have a field in **Group/Color**, you can't have more than one field under **Bars**. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/combo-chart-example2-clustered.png) 1. (Optional) Add drill-down layers by dragging one or more additional fields to the **X axis** or **Group/Color** field wells. For more information about adding drill-downs, see [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md). # Using custom visual content Using custom visual content You can embed webpages and online videos, forms, and images in your Quick dashboards using the custom visual content chart type. For example, you can embed the image of your company logo in your dashboards. You can also embed an online video from your organization's latest conference, or embed an online form asking readers of the dashboard if the dashboard is helpful. After you create custom visual content, you can use navigation actions to navigate within them. You can also use parameters to control what appears in them. The following limitations apply to custom visual content: + Only `https` URL schemes are supported. + Custom visual content isn't supported in email reports. + Images and websites that use hotlink protection won't load in custom visuals. To embed a webpage, video, online form, or image in your dashboard, choose the custom visual content icon in the **Visual types** pane. For more information about adding visuals to a dashboard, see [Adding a visual](creating-a-visual.md#create-a-visual). Use the following procedures to learn how to embed custom visuals in your dashboards. ## Best practices for using custom visual content Best practices When embedding web content using the custom visual content chart type, we recommend the following: + Choose web content from sources that support viewing or opening the content in an IFrame. If the source of the web content doesn't support being viewed or opened in an IFrame, the content doesn't appear in Quick, even if the URL is accurate. + When possible, use embeddable URLs, especially for videos, online forms, spreadsheets, and documents. Embeddable URLs create a better experience for readers of your dashboard and make interacting with the content easier. You can usually find the embeddable URL for content when you choose to share the content from the source website. + To embed internal URLs or URLs that you own, you might need to set them to be opened in an IFrame. + When viewing custom visual content in an analysis or dashboard, make sure you enable all cookies. If third-party cookies are blocked in your browser, images that are part of the website that is embedded within the custom content visual do not render. **Note** Chrome has announced plans to deprecate all third-party cookies by the end of 2024. This means that websites that are embedded within Quick custom content visuals will no longer show any contents that rely on third-party cookies in Chrome. For more information about Chrome's plans to deprecate third party cookies, see [Chrome is deprecating third-party cookies](https://cloud.google.com/looker/docs/best-practices/chrome-third-party-cookie-deprecation). ## Embedding images in a dashboard Embedding images You can embed an online image in a dashboard using the image URL. Use the following procedure to embed an image using the custom visual content chart type. Embedded images don't appear in a browser that has third-party cookies blocked. To see embedded images in a dashboard, enable third-party cookies in your browser settings. **To embed an image in a dashboard** 1. In the **Visual types** pane, choose the custom visual content icon. 1. In the visual, choose **Customize visual**. 1. In the **Properties** pane that opens, under **Custom content**, enter the image URL for the image that you want to embed. 1. Choose **Apply**. The image appears as a webpage in the visual. 1. Choose **Show as image**. If the URL is an image, the image appears in the visual. If the URL is not an image, such as a URL to a slide show, gallery, or webpage, the following message appears: `This URL doesn't appear to be an image. Update the URL to an image`. To do so, open the image that you want to embed in a separate browser tab, or choose an embeddable URL for the image (usually found when you choose to share the image). 1. (Optional) For **Image sizing options**, choose one of the following options: + **Fit to width** – This option fits the image to the width of the visual. + **Fit to height** – This option fits the image to the height of the visual. + **Scale to visual** – This option scales the image to the width and height of the visual. This option might contort the image. + **Do not scale** – This option keeps the image at its original scale and doesn't fit the image to the dimensions of the visual. With this option, the image is centered in the visual and the parts of the image that are within the width and height of the visual appear. Some parts of the image might not appear if the visual is smaller than the image. If the visual is larger than the image, however, the image is centered in the visual and is surrounded by white space. ## Embedding online forms in a dashboard Embedding online forms You can embed an online form in a dashboard using the embeddable URL. Use the following procedure to embed an online form using the custom visual content chart type. **To embed an online form in a dashboard** 1. In the **Visual types** pane, choose the custom visual content icon. 1. In the visual, choose **Customize visual**. 1. In the **Properties** pane that opens, under **Custom content**, enter the form URL for the online form that you want to embed. If possible, use an embeddable URL for the form. Using an embeddable URL creates a better experience for readers of your dashboard who might want to interact with the form. You can often find the embeddable URL when you choose to share the form on the site where you create it. 1. Choose **Apply**. The form appears in the visual. ## Embedding webpages in a dashboard Embedding webpages You can embed webpage in a dashboard using the URL. Use the following procedure to embed webpage using the custom visual content chart type. **To embed a webpage in a dashboard** 1. In the **Visual types** pane, choose the custom visual content icon. 1. In the visual, choose **Customize visual**. 1. In the **Properties** pane that opens, under **Custom content**, enter the URL for the webpage that you want to embed. 1. Choose **Apply**. The webpage appears in the visual. ## Embedding online videos in a dashboard Embedding online videos You can embed an online video in a dashboard using the embeddable video URL. Use the following procedure to embed an online video using the custom visual content chart type. **To embed an online video in a dashboard** 1. In the **Visual types** pane, choose the custom visual content icon. 1. In the visual, choose **Customize visual**. 1. In the **Properties** pane that opens, under **Custom content**, enter the embeddable URL for the video that you want to embed. To find the embeddable URL for a video, share the video and copy the embed URL from IFrame code. The following is an example of an embed URL for a YouTube video: `https://www.youtube.com/embed/uniqueid`. For a Vimeo video, the following is an example of an embed URL: `https://player.vimeo.com/video/uniqueid`. 1. Choose **Apply**. The video appears in the visual. # Using donut charts Use donut charts to compare values for items in a dimension. The best use for this type of chart is to show a percentage of a total amount. Each wedge in a donut chart represents one value in a dimension. The size of the wedge represents the proportion of the value for the selected measure that the item represents compared to the whole for the dimension. Donut charts are best when precision isn't important and there are few items in the dimension. To learn how to use donut charts in Amazon Quick, you can watch this video: [![AWS Videos](http://img.youtube.com/vi/vR6H4bXaRBY/0.jpg)](http://www.youtube.com/watch?v=vR6H4bXaRBY) To create a donut chart, use one dimension in the **Group/Color** field well. With only one field, the chart displays the division of values by row count. To display the division of dimension values by a metric value, you can add a metric field to the **Value** field well. Donut charts show up to 20 data points for group or color. For more information about how Amazon Quick handles data that falls outside display limits, see [Display limits](working-with-visual-types.md#display-limits). ## Donut chart features To understand the features supported by donut charts, use the following table. **** | Feature | Supported? | Comments | For more information | | --- | --- | --- | --- | | Changing the legend display | Yes | | [Legends on visual types in Quick](customizing-visual-legend.md) | | Changing the title display | Yes | | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Changing the axis range | Not applicable | | [Range and scale on visual types in Quick](changing-visual-scale-axis-range.md) | | Changing the visual colors | Yes | | [Colors in visual types in Quick](changing-visual-colors.md) | | Focusing on or excluding elements | Yes, with exceptions | You can focus on or exclude a wedge in a donut chart, except when you are using a date field as a dimension. In that case, you can only focus on a wedge, not exclude it. | [Focusing on visual elements](focusing-on-visual-elements.md) [Excluding visual elements](excluding-visual-elements.md) | | Sorting | Yes | You can sort on the field that you choose for the value or the group or color. | [Sorting visual data in Amazon Quick](sorting-visual-data.md) | | Performing field aggregation | Yes | You must apply aggregation to the field that you choose for the value, and can't apply aggregation to the field that you choose for group or color. | [Changing field aggregation](changing-field-aggregation.md) | | Adding drill-downs | Yes | You can add drill-down levels to the Group/Color field well. | [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md) | | Choosing size | Yes | You can choose how thick the donut chart is: small, medium, and large. | [Formatting in Amazon Quick](formatting-a-visual.md) | | Showing totals | Yes | You can choose to display or hide the aggregate of the Value field. By default, this displays the total count of the Group/Color field, or the total sum of the Value field. | [Formatting in Amazon Quick](formatting-a-visual.md) | ## Creating a donut chart Use the following procedure to create a donut chart. **To create a donut chart** 1. On the analysis page, choose **Visualize** on the tool bar. 1. Choose **Add** on the application bar, and then choose **Add visual**. 1. On the **Visual types** pane, choose the donut chart icon. 1. From the **Fields list** pane, drag the fields that you want to use to the appropriate field wells. Typically, you want to use dimension or measure fields as indicated by the target field well. If you choose to use a dimension field as a measure, the **Count** aggregate function is automatically applied to it to create a numeric value. To create a donut chart, drag a dimension to the **Group/Color** field well. Optionally, drag a measure to the **Value** field well. 1. (Optional) Add drill-down layers by dragging one or more additional fields to the **Group/Color** field well. For more information about adding drill-downs, see [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md). # Using funnel charts Use a funnel chart to visualize data that moves across multiple stages in a linear process. In a funnel chart, each stage of a process is represented in blocks of different shapes and colors. The first stage, known as the *head*, is the largest block and is followed by the smaller stages, known as the *neck*, in a funnel shape. The size of the block representing each stage in a funnel chart is a percentage of the total, and is proportionate to its value. The bigger the size of the block, the bigger its value. Funnel charts are often useful in business contexts because you can view trends or potential problem areas in each stage, such as bottlenecks. For example, they can help you visualize the amount of the potential revenue in each stage of a sale, from first contact to final sale and on through maintenance. **To create a basic funnel chart visual** 1. Open Amazon Quick and choose **Analyses** on the navigation pane at left. 1. Choose one of the following: + To create a new analysis, choose **New analysis** at upper right. For more information, see [Starting an analysis in Quick Sight](creating-an-analysis.md). + To use an existing analysis, choose the analysis that you want to edit. 1. Choose **Add (\$1), Add Visual**. 1. At lower left, choose the funnel chart icon from **Visual types**. 1. On the **Fields list** pane, choose the fields that you want to use for the appropriate field wells. Funnel charts require one dimension in **Group**. 1. (Optional) Add drill-down layers by dragging one or more additional fields to the **Group/Color** field well. For more information about adding drill-downs, see [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md). To understand the features supported by funnel charts, see [Analytics formatting per type in Quick](analytics-format-options.md). For customization options, see [Formatting in Amazon Quick](formatting-a-visual.md). # Using gauge charts Use gauge charts to compare values for items in a measure. You can compare them to another measure or to a custom amount. A gauge chart is similar to a nondigital gauge, for example a gas gauge in an automobile. It displays how much there is of the thing you are measuring. In a gauge chart, this measurement can exist alone or in relation to another measurement. Each color section in a gauge chart represents one value. In the following example, we are comparing actual sales to the sales goal, and the gauge shows that we must sell an additional 33.27% to meet the goal. To learn how to use gauge charts in Amazon Quick, you can watch this video: [![AWS Videos](http://img.youtube.com/vi/03gYx4-iGak/0.jpg)](http://www.youtube.com/watch?v=03gYx4-iGak) To create a gauge chart, you need to use at least one measure. Put the measure in the **Value** field well. If you want to compare two measures, put the additional measure in the **Target value** field well. If you want to compare a single measure to a target value that isn't in your dataset, you can use a calculated field that contains a fixed value. You can choose a variety of formatting options for the gauge chart, including the following settings in **Format visual**. + ****Value displayed**** – Hide value, display actual value, or display a comparison of two values + ****Comparison method**** – Compare values as a percent, the actual difference between values, or difference as a percent + ****Axis style**** – + **Show axis label** – Show or hide the axis label + **Range** – The numeric minimum and maximum range to display in the gauge chart + **Reserve padding (%)** – Added to the top of the range (target, actual value, or max) + ****Arc style**** – Degrees the arc displays (180° to 360°) + ****Thickness**** – Thickness of the arc (small, medial, or large) ## Gauge chart features To understand the features supported by gauge charts, use the following table. **** | Feature | Supported? | Comments | For more information | | --- | --- | --- | --- | | Changing the legend display | Yes | | [Legends on visual types in Quick](customizing-visual-legend.md) | | Changing the title display | Yes | | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Formatting gauge | Yes | You can customize the value displayed, the comparison method, the axis style, the arc style, and the thickness of the gauge. | | | Changing the axis range | No | | | | Changing the visual colors | Yes | The foreground color the filled area; it represents the Value. The background color the unfilled area; it represents the Target value if one is selected. | [Colors in visual types in Quick](changing-visual-colors.md) | | Focusing on or excluding elements | No | | | | Sorting | No | | [Sorting visual data in Amazon Quick](sorting-visual-data.md) | | Performing field aggregation | Yes | | [Changing field aggregation](changing-field-aggregation.md) | | Adding drill-downs | No | | | ## Creating a gauge chart Use the following procedure to create a gauge chart. **To create a gauge chart** 1. On the analysis page, choose **Visualize** on the tool bar. 1. Choose **Add** on the application bar, and then choose **Add visual**. 1. On the **Visual types** pane, choose the gauge chart icon. 1. From the **Fields list** pane, drag the fields that you want to use to the appropriate field wells. To create a gauge chart, drag a measure to the **Value** field well. To add a comparison value, drag a different measure to the **Target value** field well. # Using heat maps Use heat maps to show a measure for the intersection of two dimensions, with color-coding to easily differentiate where values fall in the range. Heat maps can also be used to show the count of values for the intersection of the two dimensions. Each rectangle on a heat map represents the value for the specified measure for the intersection of the selected dimensions. Rectangle color represents where the value falls in the range for the measure, with darker colors indicating higher values and lighter colors indicating lower ones. Heat maps and pivot tables display data in a similar tabular fashion. Use a heat map if you want to identify trends and outliers, because the use of color makes these easier to spot. Use a pivot table if you want to further analyze data on the visual, for example by changing column sort order or applying aggregate functions across rows or columns. To create a heat map, choose at least two fields of any data type. Amazon Quick populates the rectangle values with the count of the x-axis value for the intersecting y-axis value. Typically, you choose a measure and two dimensions. Heat maps show up to 50 data points for rows and up to 50 data points for columns. For more information about how Amazon Quick handles data that falls outside display limits, see [Display limits](working-with-visual-types.md#display-limits). ## Heat map features To understand the features supported by heat maps, use the following table. | Feature | Supported? | Comments | For more information | | --- | --- | --- | --- | | Changing the legend display | Yes | | [Legends on visual types in Quick](customizing-visual-legend.md) | | Changing the title display | Yes | | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Changing the axis range | Not applicable | | [Range and scale on visual types in Quick](changing-visual-scale-axis-range.md) | | Changing the visual colors | No | | [Colors in visual types in Quick](changing-visual-colors.md) | | Focusing on or excluding elements | Yes, with exceptions | You can focus on or exclude a rectangle in a heat map, except when you are using a date field as the rows dimension. In that case, you can only focus on a rectangle, not exclude it. | [Focusing on visual elements](focusing-on-visual-elements.md) [Excluding visual elements](excluding-visual-elements.md) | | Sorting | Yes | You can sort by the fields you choose for the columns and the values. | [Sorting visual data in Amazon Quick](sorting-visual-data.md) | | Performing field aggregation | Yes | You must apply aggregation to the fields you choose for the value, and can't apply aggregation to the fields you choose for the rows or columns. | [Changing field aggregation](changing-field-aggregation.md) | | Adding drill-downs | Yes | You can add drill-down levels to the Rows and Columns field wells. | [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md) | | Conditional formatting | No | | [Conditional formatting on visual types in Quick](conditional-formatting-for-visuals.md) | ## Creating a heat map Use the following procedure to create a heat map. **To create a heat map** 1. On the analysis page, choose **Visualize** on the tool bar. 1. Choose **Add** on the application bar, and then choose **Add visual**. 1. On the **Visual types** pane, choose the heat map icon. 1. From the **Fields list** pane, drag the fields that you want to use to the appropriate field wells. Typically, you want to use dimension or measure fields as indicated by the target field well. If you choose to use a dimension field as a measure, the **Count** aggregate function is automatically applied to it to create a numeric value. To create a heat map, drag a dimension to the **Rows** field well, a dimension to the **Columns** field well, and a measure to the **Values** field well. 1. (Optional) Add drill-down layers by dragging one or more additional fields to the **Rows** or **Columns** field wells. For more information about adding drill-downs, see [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md). # Using Highcharts Use Highcharts visuals to create custom chart types and visuals that use the [Highcharts Core library](https://www.highcharts.com/blog/products/highcharts/). Highcharts visuals provide Quick authors direct access to the [Highcharts API](https://api.highcharts.com/highcharts/). To configure a Highcharts visual, Quick authors need to add a Highcharts JSON schema to the visual in Quick. Authors can use Quick expressions to reference Quick fields, and formatting options in the JSON schema that they use to generate the Highcharts visual. The JSON **Chart code** editor provides contextual assistance for autocomplete and real time validation to ensure that the input JSON schemas are configured properly. To maintain security, the Highcharts visual editor does not accept CSS, JavaScript, or HTML code input. For more information about Highcharts visuals in Amazon Quick, see the [Highcharts Visual QuickStart Guide](https://democentral.learnquicksight.online/#Dashboard-FeatureDemo-Highcharts-Visual) in [DemoCentral](https://democentral.learnquicksight.online/#). The following image shows a lipstick chart that is configured in the **Chart code** JSON editor of a Highcharts visual in Quick. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/highcharts-example1.png) For more examples of visuals that you can create with the Highcharts visual in Quick, see [Highcharts demos](https://www.highcharts.com/demo). ## Considerations Before you start creating Highcharts visuals in Amazon Quick, review the following limitations that apply to Highcharts visuals. + The following JSON values are not supported in the Highcharts **Chart code** JSON editor: + Functions + Dates + Undefined values + Links to GeoJSON files or other images are not supported for Highcharts visuals. + Field colors are not available for Highcharts visuals. Default theme colors are applied to all Highcharts visuals. ## Creating a Highcharts visual Use the following procedure to create a Highcharts visual in Amazon Quick. 1. Open the [Quick console](https://quicksight.aws.amazon.com/). 1. Open the Quick analysis that you want to add a Highcharts visual to. 1. On the application bar, choose **Add**, and then choose **Add visual**. 1. On the **Visual types** pane, choose the Highcharts visual icon. An empty visual appears on the analysis sheet and the **Properties** pane opens on the left. 1. In the **Properties** pane, expand the **Display settings** section and perform the following actions: 1. For **Edit title**, choose the paintbrush icon, enter the title that you want the visual to have, and then choose **SAVE**. Alternatively, choose the eyeball icon to hide the title. 1. (Optional) For **Edit subtitle**, choose the paintbrush icon, enter the subtitle that you want the visual to have, and then choose **SAVE**. Alternatively, choose the eyeball icon to hide the subtitle. 1. (Optional) For **Alt text**, add the alt text that you want the visual to have. 1. Expand the **Data point limit** section. For **Number of data points to show**, enter the number of data points that you want the visual to show. Highcharts visuals can show up to 10,000 data points. 1. Expand the **Chart code** section. 1. Enter a JSON schema into the **Chart code** JSON editor. The editor provides contextual assistance and real time validation to ensure that your input JSON is configured properly. Any errors that Quick identifies can be viewed in the **Errors** dropdown. The example below shows a JSON schema that creates a lipstick chart that shows current year sales by industry. ``` { "xAxis": { "categories": ["getColumn", 0] }, "yAxis": { "min": 0, "title": { "text": "Amount ($)" } }, "tooltip": { "headerFormat": "{point.key}", "pointFormat": "", "footerFormat": "
{series.name}: ${point.y:,.0f}
", "shared": true, "useHTML": true }, "plotOptions": { "column": { "borderWidth": 0, "grouping": false, "shadow": false } }, "series": [ { "type": "column", "name": "Current Year Sales", "color": "rgba(124,181,236,1)", "data": ["getColumn", 1], "pointPadding": 0.3, "pointPlacement": 0.0 } ] } ``` 1. Choose **APPLY CODE**. Quick converts the JSON schema into a visual that appears in the analysis. To make changes to the rendered visual, update the appropriate properties in the JSON schema and choose **APPLY CODE**. 1. (Optional) Open the **Reference** dropdown to access links to helpful Highctarts reference material. When you are happy with the rendered visual, close the properties pane. For more information about Quick Sight specific expressions that can be used to configure a Highcharts visual, see [Amazon Quick JSON expression language for Highcharts visuals](highchart-expressions.md). ## Interactive Highchart features Highchart visualizations in Amazon Quick Sight support custom actions, highlighting, and custom field color consistencies, allowing you to create interactive and visually cohesive charts that integrate seamlessly with other Quick Sight visuals. ### Custom actions With custom actions, you can define specific behaviors for any data point in your Highchart visualizations. This feature seamlessly integrates with Quick Sight's existing action framework, enabling you to create interactive charts that respond to user clicks. The system currently supports single data point selection, giving you precise control over user interactions. Custom actions can be implemented across various chart types, including line charts, bar charts, and stacked bar charts, among others. To implement custom actions, you'll need to modify your Highcharts JSON configuration. Add an event block to your series configuration, specifying the click event and the corresponding action. For example: ``` { "series": [{ "type": "line", "data": ["getColumn", 1], "name": "value", "events": { "click": [ "triggerClick", { "rowIndex": "point.index" } ] } }] ``` This configuration enables click events on your chart's data points, allowing Quick Sight to handle custom actions based on the selected data. ### Cross-visual highlighting Cross-visual highlighting enhances the interactivity of your dashboards by creating visual connections between different charts. When a user selects elements in one chart, related elements in other visuals are automatically highlighted, while unrelated elements are dimmed. This feature helps users quickly identify relationships and patterns across multiple visualizations, improving data comprehension and analysis. To enable cross-visual highlighting and maintain field color consistency, use the `quicksight` clause in your Highcharts JSON configuration. This clause acts as a bridge between Highcharts rendering and Quick's visual interaction system. Here's an example of how to set it up: ``` { "quicksight": { "pointRender": ["updatePointAttributes", { "opacity": ["case", ["dataMarkMatch", ["getColumnName", 0], "series.name"], 1, // Full opacity for matching elements 0.1 // Dim non-matching elements ], "color": ["getColumnColorOverrides", ["getColumnName", 0], "series.name"] }] } } ``` This configuration uses Quick Sight's JSON expression language to dynamically modify visual properties like opacity and color based on user interactions and predefined color schemes. For more complex scenarios, you can set up highlighting based on multiple conditions. This allows for more nuanced interactivity in your visualizations. The following example highlights elements based on either the quarter or day of the week: ``` { "quicksight": { "pointRender": ["updatePointAttributes", { "opacity": ["case", ["||", ["dataMarkMatch", "quarter", "series.name"], ["dataMarkMatch", "day_of_week", "point.name"] ], 1, // Full opacity for matching elements 0.1 // Dim non-matching elements ], }] } } ``` ### Field-level color consistency Maintaining visual coherence across your dashboard is crucial for effective data interpretation. The field-level color consistency feature ensures that colors assigned to specific dimensions perist across all visuals in your dashboard. This consistency helps users quickly recognize and track particular data categories across different chart types and views, enhancing the overall user experience and data comprehension. # Amazon Quick JSON expression language for Highcharts visuals JSON expression language for Highcharts Highcharts visuals accept most [valid JSON values](https://www.w3schools.com/js/js_json_datatypes.asp), standard arithmetic operators, string operators, and conditional operators. The following JSON values are not supported for Highcharts visuals: + Functions + Dates + Undefined values Quick authors can use JSON expression language create JSON schemas for a highcharts visual. JSON expression language is used to bind JSON to APIs or datasets to allow dynamic population and modification of JSON structures. Developers can also use JSON expression language to inflate and transform JSON data with concise and intuitive expressions. With JSON expression language, expressions are represented as arrays, where the first element specifies the operation and subsequent elements are the arguments. For example, `["unique", [1, 2, 2]]` applies the `unique` operation to the array `[1, 2, 2]`, resulting in `[1, 2]`. This array-based syntax allows for flexible expressions, that allow complex transformations on JSON data. JSON expression language supports *nested expressions*. Nested expressions are expressions that contain other expressions as arguments. For example `["split", ["toUpper", "hello world"], " "]` first converts the string `hello world` into an uppercase, then splits it into array of words, resulting in `["HELLO", "WORLD"]`. Use the following sections to learn more about JSON expression language for Highcharts visuals in Amazon Quick. **Topics** + [ # Arithmetics ](jle-arithmetics.md) + [ # Array operations ](jle-arrays.md) + [ # Amazon Quick expressions ](jle-qs-expressions.md) # Arithmetics The following table shows arithmetic expressions that can be used with JSON expression language. | Operation | Expression | Input | Output | | --- | --- | --- | --- | | Addition | ["\$1", operand1, operand2] | \$1 sum: ["\$1", 2, 4] \$1 | \$1 sum: 6 \$1 | | Subtraction | ["-", operand1, operand2] | \$1 difference: ["-", 10, 3] \$1 | \$1 difference: 7 \$1 | | Multiplication | ["\$1", operand1, operand2] | \$1 product: ["\$1", 5, 6] \$1 | \$1 product: 30 \$1 | | Division | ["/", operand1, operand2] | \$1 quotient: ["/", 20, 4] \$1 | \$1 quotient: 5 \$1 | | Modulo | ["%", operand1, operand2] | \$1 remainder: ["%", 15, 4] \$1 | \$1 remainder: 3 \$1 | | Exponentiation | ["\$1\$1", base, exponent] | \$1 power: ["\$1\$1", 2, 3] \$1 | \$1 power: 8 \$1 | | Absolute Value | ["abs", operand] | \$1 absolute: ["abs", -5] \$1 | \$1 absolute: 5 \$1 | | Square Root | ["sqrt", operand] | \$1 sqroot: ["sqrt", 16] \$1 | \$1 sqroot: 4 \$1 | | Logarithm (base 10) | ["log10", operand] | \$1 log: ["log10", 100] \$1 | \$1 log: 2 \$1 | | Natural Logarithm | ["ln", operand] | \$1 ln: ["ln", Math.E] \$1 | \$1 ln: 1 \$1 | | Round | ["round", operand] | \$1 rounded: ["round", 3.7] \$1 | \$1 rounded: 4 \$1 | | Floor | ["floor", operand] | \$1 floor: ["floor", 3.7] \$1 | \$1 floor: 3 \$1 | | Ceiling | ["ceil", operand] | \$1 ceiling: ["ceil", 3.2] \$1 | \$1 ceiling: 4 \$1 | | Sine | ["sin", operand] | \$1 sine: ["sin", 0] \$1 | \$1 sine: 0 \$1 | | Cosine | ["cos", operand] | \$1 cosine: ["cos", 0] \$1 | \$1 cosine: 1 \$1 | | Tangent | ["tan", operand] | \$1 tangent: ["tan", Math.PI] \$1 | \$1 tangent: 0 \$1 | # Array operations JSON expression language allows generic array manipulation for the following functions: + `map` – Applies a mapping function to each element of an array and returns a new array with the transformed values. For example, `["map", [1, 2, 3], ["*", ["item"], 2]]` maps each element of the array `[1, 2, 3]` by multiplying it by 2. + `filter` – Filters an array based on a given condition and returns a new array containing only the elements that satisfy the condition For example, `["filter", [1, 2, 3, 4, 5], ["==", ["%", ["item"], 2], 0]]` filters the array `[1, 2, 3, 4, 5]` to include only the even numbers. + `reduce` – Reduces an array to a single value by applying a reducer function to each element and accumulating the result. For example, `["reduce", [1, 2, 3, 4, 5], ["+", ["acc"], ["item"]], 0]` reduces the array `[1, 2, 3, 4, 5]` to the sum of its elements. + `get` – Retrieves a value from an object or an array by specifying a key or index. For example, `["get", ["item"], "name"]` retrieves the value of the `"name"` property from the current item. + `unique` – Given an array returns only unique items inside this array. For example, `["unique", [1, 2, 2]]` returns `[1, 2]`. # Amazon Quick expressions Amazon Quick offers additional expressions to enhance the functionality of Highcharts visuals. Use the following sections to learn more about common Quick expressions for highcharts visuals. For more information about JSON expression language in Amazon Quick, see the [Highcharts Visual QuickStart Guide](https://democentral.learnquicksight.online/#Dashboard-FeatureDemo-Highcharts-Visual) in [DemoCentral](https://democentral.learnquicksight.online/#). **Topics** + [ ## `getColumn` ](#highcharts-expressions-getcolumn) + [ ## `formatValue` ](#highcharts-expressions-formatvalue) ## `getColumn` Use the `getColumn` expressions to return values from specified column indices. For example, the following table shows a list of products alongside their category, and price. | Product name | Category | Price | | --- | --- | --- | | Product A | Technology | 100 | | Product B | Retail | 50 | | Product C | Retail | 75 | The following `getColumn` query generates an array that shows all product names alongside their price. ``` { product name: ["getColumn", 0], price: ["getColumn", 2] } ``` The follwing JSON is returned: ``` { product name: ["Product A", "Product B", "Product C"], price: [100, 50, 75] } ``` You can also pass multiple columns at once to generate an array of arrays, shown in the following example. **Input** ``` { values: ["getColumn", 0, 2] } ``` **Output** ``` { values: [["Product A", 100], ["Product B", 50], ["Product C", 75]] } ``` Similar to `getColumn`, the following expressions can be used to return column values from field wells or themes: + `getColumnFromGroupBy` returns columns from the group by field. The second argument is the index of the column to return. For example, `["getColumnFromGroupBy", 0]` returns values of the first field as an array. You can pass multiple indices to get an array of arrays where each element corresponds to the field in the group by field well. + `getColumnFromValue` returns columns from the value field well. You can pass multiple indices to get an array of arrays where each element corresponds to the field in the values field well. + `getColorTheme` returns the current color pallete of a Quick theme, shown in the following example. ``` { "color": ["getColorTheme"] } ``` ``` { "color": ["getPaletteColor", "secondaryBackground"] } ``` **Example** ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/get-column-example.png) `getColumn` can access any column from the table: + `["getColumn", 0]` - returns array `[1, 2, 3, 4, 5, ...]` + `["getColumn", 1]` - returns array `[1, 1, 1, 1, 1, ...]` + `["getColumn", 2]` - returns array `[1674, 7425, 4371, ...]` `getColumnFromGroupBy` works similarly, but its index is limited to the columns in the group by field well: + `["getColumnFromGroupBy", 0]` - returns array `[1, 2, 3, 4, 5, ...]` + `["getColumnFromGroupBy", 1]` - returns array `[1, 1, 1, 1, 1, ...]` + `["getColumnFromGroupBy", 2]` - does not work, since there are only two columns in the group by field well `getColumnFromValue` works similarly, but its index is limited to the columns in the value field well: + `["getColumnFromValue", 0]` - returns array `[1, 2, 3, 4, 5, ...]` + `["getColumnFromValue", 1]` - does not work, since there is only one column in the value field well + `["getColumnFromValue", 2]` - does not work, since there is only one column in the value field well ## `formatValue` Use the `formatValue` expression to apply Quick formatting to your values. For example, the following expression formats the x-axis label with the format value that is specified in the first field of Quick field wells. ``` "xAxis": { "categories": ["getColumn", 0], "labels": { "formatter": ["formatValue", "value", 0] } } ``` # Using histograms Use a histogram chart in Amazon Quick to display the distribution of continuous numerical values in your data. Amazon Quick uses un-normalized histograms, which use an absolute count of the data points or events in each bin. To create a histogram, you use one measure. A new histogram initially displays ten *bins* (also called *buckets*) across the X-axis. These appear as bars on the chart. You can customize the bins to suit your dataset. The Y-axis displays the absolute count of the values in each bin. Make sure that you adjust the format settings so that you have a clearly identifiable shape. If your data contains outliers, this becomes clear if you spot one or more values off to the side of the X-axis. For information about how Amazon Quick handles data that falls outside display limits, see [Display limits](working-with-visual-types.md#display-limits). ## Histogram features To understand the features supported by histograms, use the following table. **** | Feature | Supported? | Comments | For more information | | --- | --- | --- | --- | | Changing the legend display | No | | [Legends on visual types in Quick](customizing-visual-legend.md) | | Changing the title display | Yes | | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Changing the axis range | No | However, you can change the bin count or the bin interval width (range of distribution). | | | Showing or hiding axis lines, grid lines, axis labels, and axis sort icons | Yes | | [Axes and grid lines on visual types in Quick](showing-hiding-axis-grid-tick.md) | | Changing the visual colors | Yes | | [Colors in visual types in Quick](changing-visual-colors.md) | | Focusing on or excluding elements | No | | | | Sorting | No | | | | Performing field aggregation | No | Histograms use only the count aggregation. | | | Adding drill-downs | No | | | ## Creating a histogram Use the following procedure to create a histogram. **To create a histogram** 1. On the analysis page, choose **Visualize** on the tool bar. 1. Choose **Add** on the application bar, and then choose **Add visual**. 1. On the **Visual types** pane, choose the histogram icon. 1. On the **Fields list** pane, choose the field that you want to use in the **Value** field well. A **Count** aggregate is automatically applied to the value. The resulting histogram shows the following: + The X-axis displays 10 bins by default, representing the intervals in the measure that you choose. You can customize the bins in the next step. + The Y-axis displays the absolute count of individual values in each bin. 1. (Optional) Choose **Format** on the visual control to change the histogram format. You can format the bins either by count or width, not both together. The count setting changes how many bins display. The width setting changes how wide or long of an interval each bin contains. ## Formatting a histogram Use the following procedure to format a histogram. **To format a histogram** 1. Choose the histogram chart that you want to work with. It should be the highlighted selection. The visual controls display on the top right of the histogram. 1. Choose the cog icon on the visual control menu to view the **Format visual** options. 1. On the **Properties** pane, set the following options to control the display of the histogram: + **Histogram** settings. Chose *one* of the following settings: + Bin count (option 1): The number of bins that display on the X-axis. + Bin width (option 1): The width (or length) of each interval. This setting controls the number of items or events to include in each bin. For example, if your data is in minutes, you can set this to 10 to show 10-minute intervals. + With the following settings, you can explore the best way to format the histogram for your dataset. For example, in some cases, you might have a tall peak in one bin, while most of the other bins look sparse. This isn't a useful view. You can use the following settings individually or together: + Change the **Number of data points displayed** in the **X-axis** settings. Amazon Quick displays up to 100 bins (buckets) by default. If you want to display more (up to 1,000), change the X-axis setting for **Number of data points displayed**. + Enable **Logarithmic scale** in the **Y-axis** settings. Sometimes your data doesn't fit the shape that you want and this can provide misleading results. For example, if the shape is skewed so far to the right that you can't read it properly, you can apply a log scale to it. Doing this doesn't normalize your data; however, it does reduce the skew. + Display **Data labels**. You can enable the display of data labels to see the absolute counts in the chart. Even if you don't want to display these in most cases, you can enable them while you're developing an analysis. The labels can help you decide on formatting and filtering options because they reveal counts in bins that are too small to stand out. To see all the data labels, even if they overlap, enable **Allow labels to overlap**. 1. (Optional) Change other visual settings. For more information, see [Formatting in Amazon Quick](formatting-a-visual.md). ## Understanding histograms Although histograms look similar to bar charts, they are very different. In fact, the only similarity is their appearance because they use bars. On a histogram, each bar is called a *bin* or a *bucket*. Each bin contains a range of values called an *interval*. When you pause on one of the bins, details about the interval appear in a tooltip that shows two numbers enclosed in glyphs. The type of enclosing glyphs indicates if the numbers inside them are part of the interval that's inside the selected bin, as follows: + A square bracket next to a number means that the number is included. + A parenthesis next to a number means that the number is excluded. For example, let's say that the first bar in a histogram displays the following notation. ``` [1, 10) ``` The square bracket means that the number 1 is included in the first interval. The parenthesis means that the number 10 is excluded. In the same histogram, a second bar displays the following notation. ``` [10, 20) ``` In this case, 10 is included in the second interval, and 20 is excluded. The number 10 can't exist in both intervals, so the notation shows us which one includes it. **Note** The pattern used for marking intervals in a histogram comes from standard mathematical notation. The following examples show the possible patterns, using a set of numbers that includes 10, 20, and every number in between. [10, 20] – This set is closed. It has hard boundaries on both ends. [10, 21) – This set is half open. It has a hard boundary on the left and a soft boundary on the right. (9, 20] – This set is half open. It has a soft boundary on the left and a hard boundary on the right. (9, 21) – This set is open. It has soft boundaries on both ends. Because the histogram uses quantitative data (numbers) rather than qualitative data, there's a logical order to the distribution of the data. This is called a *shape*. The shape is often described the qualities the shape possesses, based on the count in each bin. Bins that contain a higher number of values form a *peak*. Bins that contain a lower number of values form a *tail* on the edge of a chart, and a *valley* between peaks. Most histograms fall into one of the following shapes: + Asymmetrical or *skewed* distributions have values that cluster near the left or the right—the low or high end of the X-axis. The direction of skewness is defined by where the longer tail of the data is, not by where the peak is. It's defined this way because this direction also describes the location of the mean (average). In skewed distributions, the mean and the median are two different numbers. The different types of skewed distribution are as follows: + *Negatively* skewed or *left* skewed – A chart that has the mean to the left of the peak. It has a longer tail to the left and a peak to the right, sometimes followed by a shorter tail. + *Positively* skewed or *right* skewed – A chart that has the mean to the right of the peak. It has a longer tail to the right and a peak to the left, sometimes preceded by a shorter tail. + Symmetrical or *normal* distributions have a shape that's mirrored on each side of a center point (for example, a bell curve). In a normal distribution, the mean and the median are the same value. The different types of normal distribution are as follows: + Normal distribution, or *unimodal* – A chart that has one central peak representing the most common value. This is commonly called a bell curve, or a Gaussian distribution. + Bimodal – A chart that has two peaks representing the most common values. + Multimodal – A chart that has three or more peaks representing the most common values. + Uniform – A chart that has no peaks or valleys, with a relatively equal distribution of data. The following table shows how a histogram differs from a bar chart. | Histogram | Bar chart | | --- | --- | | A histogram displays the distribution of values in one field. | A bar chart compares the values in one field, grouped by dimension. | | A histogram sorts values into bins that represent a range of values, for example 1–10, 10–20, and so on. | A bar chart plots values that are grouped into categories. | | The sum of all bins equals exactly 100% of the values in the filtered data. | A bar chart isn't required to display all of the available data. You can change display settings at the visual level. For example, a bar chart might show only the top 10 categories of data. | | Rearranging bars detracts from the meaning of the chart as a whole. | Bars can be in any order without changing the meaning of the chart as a whole. | | There are no spaces between the bars, to represent the fact this is continuous data. | There are spaces between the bars, to represent the fact that this is categorical data. | | If a line is included in a histogram, it represents the general shape of the data. | If a line is included in a bar chart, it's called a combo chart, and the line represents a different measure than the bars. | # Using image components Use image components to upload static images from your desktop to a Quick analysis. Each Quick analysis sheet supports up to 10 image components. Image components are not included in the 50 visual per sheet limit. The file size of an image component can't exceed 1MB. The following file formats are supported for image components: + `.bmp` + `.jpg/.jpeg` + `.png` + `.tiff` + `.webp` Use the following procedure to add an image component to a Quick analysis: **To add an image component to a Quick analysis** 1. Open the [Quick console](https://quicksight.aws.amazon.com/). 1. Open the Quick analysis that you want to add an image to. 1. Choose the **Add image** button in the toolbar at the top of the analysis. 1. The file selection of your desktop opens. Choose the file that you want to upload, and then choose **Open**. The file size of the image component can't exceed 1MB. 1. The image is uploaded to Quick and appears in the analysis. 1. (Optional) To add alt text or update the image scaling options, choose the **Properties** icon at the top right of the image to open the **Properties** pane. 1. (Optional) To add a [custom tooltip](https://docs.amazonaws.cn/quicksuite/latest/userguide/customizing-visual-tooltips) to the image, open the **Properties** pane, choose **Interactions**, and then choose **Add action**. Filter actions are not supported for image components. You can also use the **Interactions** section to add custom navigation and URL actions to the image component. 1. (Optional) To duplicate or replace the image, choose the **More options** ellipsis (three dots) icon at the top right of the image, and then choose the action that you want to perform. # Using KPIs Use a key performance indicator (KPI) to visualize a comparison between a key value and its target value. A KPI displays a value comparison, the two values being compared, and a visual that provides context to the data that's displayed. You can choose from a set of predesigned layouts to suit your business needs. The following image shows an example of a KPI visual that uses a sparkline. 1. Choose **Add (\$1)** drop down in the **Visuals pane.** 1. Choose the KPI icon from Visual types menu. ## KPI features To understand the features supported by the KPI visual type in Amazon Quick, use the following table. | Feature | Supported? | Comments | For more information | | --- | --- | --- | --- | | Changing the title display | Yes | | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Removing the title | Yes | You can choose not to display a title. | | | Changing comparison method | Yes | By default, Amazon Quick automatically chooses a method. The settings are auto, difference, percent, and difference as percent. | | | Changing the primary value displayed | Yes | You can choose comparison (default) or actual. | | | Displaying or removing the progress bar | Yes | You can format the visual to either display (default) or not display a progress bar. | | For more information on KPI formatting options, see [KPI options](KPI-options.md). ## Creating a KPI Use the following procedure to create a KPI. **To create a KPI** 1. Create a new analysis for your dataset. 1. In the **Visual types** pane, choose the KPI icon. 1. From the **Fields list** pane, drag the fields that you want to use to the appropriate field wells. You must use measure fields as indicated by the target field well. If you choose to use a dimension field as a measure, the **Count** aggregate function is automatically applied to it to create a numeric value. To create a KPI, drag a measure to the **Value** field well. To compare that value to a target value, drag a different measure to the **Target value** field well. 1. (Optional) Choose formatting options by selecting the on-visual menu at the upper-right corner of the visual, then choosing **Format visual**. ## Changing a KPI's layout Use the following procedure to change the layout for a KPI. **To change the layout of a KPI** 1. Navigate to the KPI visual that you want to change and choose **KPI layouts**. 1. In the **KPI Layouts** pane, choose the KPI layout that you want to use. # Using layer maps Use layer maps to visualize data with custom geographic boundaries, such as congressional districts, sales territories, or user-defined regions. With layer maps, Quick authors upload GeoJSON files to Amazon Quick that shape layers over a base map and join with Quick data to visualize associated metrics and dimensions. Shape layers can be styled by color, border, and opacity. Quick authors can also add interactivity to layer maps through tooltips and custom actions. **Note** Amazon Quick layer map visuals only support polygon shapes. Line and point geometries are not supported. The following image shows a layer map visual in Amazon Quick. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/layer-map.png) ## Creating a shape layer with layered maps Use the procedure below to create a shape layer with layer map visuals in Amazon Quick. 1. Open the [Quick console](https://quicksight.aws.amazon.com/). 1. Open the Quick analysis that you want to add a layer map to. 1. Choose **Add** on the application bar, and then choose **Add visual**. 1. On the **Visual types** pane, choose one of the layer map icon. 1. An empty map visual appears in the analysis and prompts you to continue configuring the layer. Choose **CONFIGURE LAYER** to continue configuring the layer map. 1. The **Layer properties** pane opens to the right. Navigate to the **Shape file** section, and then choose **UPLOAD SHAPE FILE**. 1. Choose the GeoJSON file that you want to visualize. The file must be in `.geojson` format and must not exceed 100 MB. 1. Navigate to the **Data** section. 1. For **Shape file key field**, choose the field that you want the shape to visualize. 1. (Optional) For **Dataset key field**, choose the dataset field that you want the shape to visualize. To assign color to the shapes, add a color field. If the color field is a measure, the shape uses gradient coloring. If the color field is a dimension, the shape uses categorical coloring. If a color field is not assigned to the shape, use the fill color option in the **Styling** section of the **Layer properties** pane to set a common color for all shapes. 1. (Optional) To change the layer name, navigate to the **Layer options** section and enter a name in the **Layer name** input. 1. (Optional) To change the fill or border colors, navigate to the **Styling** section and choose the color switch next to the object that you want to change. To adjust the opacity of the color, enter a percentage amount in the input located next to the eye icon. If you do not assign a color field to the **Dataset key field**, the fill color can be used to set a common color for all shapes. # Using line charts Use line charts to compare changes in measure values over period of time, for the following scenarios: + One measure over a period of time, for example gross sales by month. + Multiple measures over a period of time, for example gross sales and net sales by month. + One measure for a dimension over a period of time, for example number of flight delays per day by airline. Line charts show the individual values of a set of measures or dimensions against the range displayed by the Y axis. Area line charts differ from regular line charts in that each value is represented by a colored area of the chart instead of just a line, to make it easier to evaluate item values relative to each other. Because a stacked area line chart works differently than other line charts, simplify it if you can. Then the audience won't try to interpret the numbers. Instead, they can focus on the relationships of each set of values to the whole. One way to simplify is to remove the numbers down the left side of the screen by reducing the step size for the axis. To do this, choose the **Options** icon from the on-visual menu. In **Format Options** under **Y-axis,** enter **2** as the **Step size**. Each line on the chart represents a measure value over a period of time. You can interactively view the values on the chart. Hover over any line to see a pop-up legend that shows the values for each line on the **X axis**. If you hover over a data point, you can see the **Value** for that specific point on the **X axis**. Use line charts to compare changes in values for one or more measures or dimensions over a period of time. In regular line charts, each value is represented by a line, and in area line charts each value is represented by a colored area of the chart. Use stacked area line charts to compare changes in values for one or more groups of measures or dimensions over a period of time. Stacked area line charts show the total value for each group on the x-axis. They use color segments to show the values of each measure or dimension in the group. Line charts show up to 10,000 data points on the x-axis when no color field is selected. When color is populated, line charts show up to 400 data points on the x-axis and up to 25 data points for color. For more information about data that falls outside the display limit for this visual type, see [Display limits](working-with-visual-types.md#display-limits). ## Line chart features To understand the features supported by line charts, use the following table. | Feature | Supported? | Comments | For more information | | --- | --- | --- | --- | | Changing the legend display | Yes | | [Legends on visual types in Quick](customizing-visual-legend.md) | | Changing the title display | Yes | | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Changing the axis range | Yes | You can set the range for the Y axis. | [Range and scale on visual types in Quick](changing-visual-scale-axis-range.md) | | Showing or hiding axis lines, grid lines, axis labels, and axis sort icons | Yes | | [Axes and grid lines on visual types in Quick](showing-hiding-axis-grid-tick.md) | | Adding a second Y-axis | Yes | | [Creating a dual-axis line chart](#dual-axis-chart) | | Changing the visual colors | Yes | | [Colors in visual types in Quick](changing-visual-colors.md) | | Focusing on or excluding elements | Yes, with exceptions | You can focus on or exclude any line on the chart, except in the following cases: [\[See the AWS documentation website for more details\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/line-charts.html) In these cases, you can only focus on a line, not exclude it. | [Focusing on visual elements](focusing-on-visual-elements.md) [Excluding visual elements](excluding-visual-elements.md) | | Sorting | Yes, with exceptions | You can sort data for numeric measures in the X axis and Value field wells. Other data is automatically sorted in ascending order. | [Sorting visual data in Amazon Quick](sorting-visual-data.md) | | Performing field aggregation | Yes | You must apply aggregation to the field that you choose for the value, and can't apply aggregation to the fields you choose for the X axis and color. | [Changing field aggregation](changing-field-aggregation.md) | | Adding drill-downs | Yes | You can add drill-down levels to the X axis and Color field wells. | [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md) | ## Creating a line chart Use the following procedure to create a line chart. **To create a line chart** 1. On the analysis page, choose **Visualize** on the tool bar. 1. Choose **Add** on the application bar, and then choose **Add visual**. 1. On the **Visual types** pane, choose one of the line chart icons. 1. From the **Fields list** pane, drag the fields that you want to use to the appropriate field wells. Typically, you want to use dimension or measure fields as indicated by the target field well. If you choose to use a dimension field as a measure, the **Count** aggregate function is automatically applied to it to create a numeric value. + To create a single-measure line chart, drag a dimension to the **X axis** field well and one measure to the **Value** field well. + To create a multi-measure line chart, drag a dimension to the **X axis** field well and two or more measures to the **Value** field well. Leave the **Color** field well empty. + To create a multi-dimension line chart, drag a dimension to the **X axis** field well, one measure to the **Value** field well, and one dimension to the **Color** field well. 1. (Optional) Add drill-down layers by dragging one or more additional fields to the **X axis** or **Color** field wells. For more information about adding drill-downs, see [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md). ## Creating a dual-axis line chart If you have two or more metrics that you want to display in the same line chart, you can create a dual-axis line chart. A *dual-axis chart* is a chart with two Y-axes (one axis at the left of the chart, and one axis at the right of the chart). For example, let's say you create a line chart. It shows the number of visitors who signed up for a mailing list and for a free service over a period of time. If the scale between those two measures varies widely over time, your chart might look something like the following line chart. Because the scale between measures varies so greatly, the measure with the smaller scale appears nearly flat at zero. ![\[Image of a line chart with two lines and one axis. One line is flat at zero.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/dual-axis-chart1.png) If you want to show these measures in the same chart, you can create a dual-axis line chart. The following is an example of the same line chart with two Y-axes. ![\[Image of the previous line chart with dual axes. Both lines are now visible.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/dual-axis-chart2.png) **To create a dual-axis line chart** 1. In your analysis, create a line chart. For more information about creating line charts, see [Creating a line chart](#create-measure-line-chart). 1. In the **Value field well**, choose a field drop-down menu, choose **Show on: Left Y-axis**, and then choose **Right Y-axis**. Or you can create a dual-axis line chart using the **Properties** pane: 1. On the menu in the upper-right corner of the line chart, choose the **Format visual** icon. 1. In the **Properties** pane that opens, choose **Data series**. 1. In the **Data series** section, choose the **Show on right axis** icon for the value that you want to place on a separate axis. Use the search bar to quickly find a value if you need to. ![\[Image of Data series section of the Format visual pane with the Show on right axis icon circled in red.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/dual-axis-chart3.png) The icon updates to indicate that the value is being shown on the right axis. The chart updates with two axes. The **Properties** pane updates with the following options: + To synchronize the Y-axes for both lines back into a single axis, choose **Single Y-axis** at the top of the **Properties** pane. + To format the axis at the left of the chart, choose **Left Y-axis**. + To format the axis at the right of the chart, choose **Right Y-axis**. For more information about formatting axis lines, see [Axes and grid lines](showing-hiding-axis-grid-tick.md). For more information about adjusting the range and scale of an axis, see [Range and scale](changing-visual-scale-axis-range.md). # Creating maps and geospatial charts You can create two types of maps in Quick: point maps and filled maps. *Point maps* show the difference between data values for each location by size. *Filled maps* show the difference between data values for each location by varying shades of color. **Important** Geospatial charts in Quick currently aren't supported in some Amazon Web Services Regions, including in China. For help with geospatial issues, see [Geospatial troubleshooting](geospatial-troubleshooting.md). Before you get started creating maps, do the following: + Make sure that your dataset contains location data. *Location data* is data that corresponds to latitudinal and longitudinal values. Location data can include a column for latitude and a column for longitude in your dataset. It can also include a column with city names. Quick can chart latitude and longitude coordinates. It also recognizes geographic components such as country, state or region, county or district, city, and ZIP code or postal code. + Make sure that your location data fields are marked as geospatial data types. + Consider creating geographic hierarchies. For more information about working with geospatial data, including changing field data types and creating geospatial hierarchies, see [Adding geospatial data](geospatial-data-prep.md). To learn more about creating maps in Quick, see the following. **Topics** + [ # Creating point maps ](point-maps.md) + [ # Creating filled maps ](filled-maps.md) + [ # Interacting with maps ](maps-interacting.md) # Creating point maps You can create point maps in Quick to show the difference between data values for each location by size. Each point on this type of map corresponds to a geographic location in your data, such as a country, state or province, or city. The size of the points on the map represents the magnitude of the field in the **Size** field well, in relation to other values in the same field. The color of the points represents the values in the **Color** field well. The field values in the **Color** field well display in the legend, if you choose a field for color. Use the following procedure to create a point map in Quick. To create point maps in Quick, make sure that you have the following: + One geospatial field (such as country, state or region, county or district, city, or ZIP code or postal code). Or you can use one latitude field and one longitude field. + One numeric field (measure) for size. + (Optional) A categorical field (dimension) for color. For information on formatting geospatial maps, see [Map and geospatial chart formatting options](https://docs.amazonaws.cn/quicksight/latest/user/geospatial-formatting). ## Creating point maps **To create a point map** 1. Add a new visual to your analysis. For more information about starting analyses, see [Starting an analysis in Quick Sight](creating-an-analysis.md). For more information about adding visuals to analyses, see [Adding a visual](creating-a-visual.md#create-a-visual). 1. For **Visual type**, choose the **Points on map** icon. It looks like a globe with a point on it. 1. Drag a geographic field from the **Fields list** pane to the **Geospatial** field well, for example `Country`. You can also choose a latitude or longitude field. A point map appears with a point for each location in your data. If the field is part of a geographic hierarchy, the hierarchy displays in the field well. 1. Drag a measure from the **Fields list** pane to the **Size** field well. The points on the map update to show the magnitude of values for each location. 1. (Optional) Drag a dimension from the **Fields list** pane to the **Color** field well. Each point updates to show a point for each categorical value in the dimension. # Creating filled maps You can create filled maps in Quick to show the difference between data values for each location by varying shades of color. Use the following procedure to create a filled map in Quick. To create filled maps in Quick, make sure that you have the following: + One geospatial field (such as country, state or region, county or district, or ZIP code or postal code). + (Optional) A numeric field (measure) for color. ## Creating filled maps **To create a filled map** 1. Add a new visual to your analysis. For more information about starting analyses, see [Starting an analysis in Quick Sight](creating-an-analysis.md). For more information about adding visuals to analyses, see [Adding a visual](creating-a-visual.md#create-a-visual). 1. For **Visual type**, choose the **Filled map** icon. 1. Drag a geographic field from the **Fields list** pane to the **Location** field well, for example `Country`. A filled map appears with each location in your data filled in by the number of times they appear in your dataset (the count). If the field is part of a geographic hierarchy, the hierarchy displays in the field well. 1. (Optional) Drag a measure from the **Fields list** pane to the **Color** field well, for example `Sales`. Each location updates to show the sum of sales. # Interacting with maps When you view a map visual in an Quick analysis or published dashboard, you can interact with it to explore your data. You can pan, zoom in and out, and autozoom to all the data. By default, map visuals are always zoomed based on the underlying data. When you pan around in the map or zoom to a different level, the zoom to data icon appears above the zoom in and out icons at bottom right of the map. Using this option, you can quickly zoom back to the underlying data. **To pan in a map visual** + Click anywhere on the map visual and drag your cursor in the direction that you want to pan the map. **To zoom in or out in a map visual** + On the map visual, choose the plus or minus icons at bottom right. Or you can double-click the map to zoom in, and shift-double-click to zoom out. **To zoom back to all the data** + On the map visual, choose the zoom to data icon. This icon appears when you pan or zoom in on a map. # Using small multiples Use this feature when you need to set multiple comparative visuals in a row. When you activate the *small multiples* feature, Amazon Quick creates a container or shelf of small visuals, presented side-by-side. Each copy of the visual contains a one view of the data. Using small multiples is a way to get a holistic view of your business, in an efficient and interactive way. Small multiples aren't listed in the palette visualization icons. Instead, the option to create small multiples appears as a field well, in the visuals that support it. **To add small visuals to your analysis** 1. On a line, bar, or pie charts, add a field to the **Small multiples** field well. 1. To see your small multiples, you need to enlarge the container that holds them, so you can see all of them at once. 1. To format the set of small multiples, choose Format visual (the pencil icon) from the menu on the visual. You can adjust the following settings: + **Layout** + **Visible rows** + **Visible columns** + **Number of panels** + Panel title options (toggle) + Font size and color + Font weight + Text alignment + **Panel order options (toggle)** Line thickness, style, and color + **Panel gutter** (toggle) **Spacing** + **Panel background** (toggle) **Background color** # Using pie charts Use pie charts to compare values for items in a dimension. The best use for this type of chart is to show a percentage of a total amount. Each wedge in a pie chart represents one item in the dimension. Wedge size represents the proportion of the value for the selected measure that the item represents compared to the whole for the dimension. Pie charts are best when precision isn't important and there are few items in the dimension. To create a donut chart, use one dimension in the **Group/Color** field well. With only one field, the chart displays the division of values by row count. To display the division of dimension values by a metric value, you can add a metric field to the **Value** field well. Pie charts show up to 20 data points for group or color. For more information about how Amazon Quick handles data that falls outside display limits, see [Display limits](working-with-visual-types.md#display-limits). ## Pie chart features To understand the features supported by pie charts, use the following table. | Feature | Supported? | Comments | For more information | | --- | --- | --- | --- | | Changing the legend display | Yes | | [Legends on visual types in Quick](customizing-visual-legend.md) | | Changing the title display | Yes | | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Changing the axis range | Not applicable | | [Range and scale on visual types in Quick](changing-visual-scale-axis-range.md) | | Showing or hiding axis labels. | Yes | | [Axes and grid lines on visual types in Quick](showing-hiding-axis-grid-tick.md) | | Changing the visual colors | Yes | | [Colors in visual types in Quick](changing-visual-colors.md) | | Focusing on or excluding elements | Yes, with exceptions | You can focus on or exclude a wedge in a pie chart, except when you are using a date field as a dimension. In that case, you can only focus on a wedge, not exclude it. | [Focusing on visual elements](focusing-on-visual-elements.md) [Excluding visual elements](excluding-visual-elements.md) | | Sorting | Yes | You can sort on the field that you choose for the value or the group or color. | [Sorting visual data in Amazon Quick](sorting-visual-data.md) | | Performing field aggregation | Yes | You must apply aggregation to the field that you choose for the value, and can't apply aggregation to the field that you choose for group or color. | [Changing field aggregation](changing-field-aggregation.md) | | Adding drill-downs | Yes | You can add drill-down levels to the Group/Color field well. | [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md) | ## Creating a pie chart Use the following procedure to create a pie chart. **To create a pie chart** 1. On the analysis page, choose **Visualize** on the tool bar. 1. Choose **Add** on the application bar, and then choose **Add visual**. 1. On the **Visual types** pane, choose the pie chart icon. 1. From the **Fields list** pane, drag the fields that you want to use to the appropriate field wells. Typically, you want to use dimension or measure fields as indicated by the target field well. If you choose to use a dimension field as a measure, the **Count** aggregate function is automatically applied to it to create a numeric value. To create a pie chart, drag a dimension to the **Group/Color** field well. Optionally, drag a measure to the **Value** field well. 1. (Optional) Add drill-down layers by dragging one or more additional fields to the **Group/Color** field well. For more information about adding drill-downs, see [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md). # Using pivot tables Use pivot tables to show measure values for the intersection of two dimensions. Heat maps and pivot tables display data in a similar tabular fashion. Use a heat map if you want to identify trends and outliers, because the use of color makes these easier to spot. Use a pivot table if you want to analyze data on the visual. To create a pivot table, choose at least one field of any data type, and choose the pivot table icon. Amazon Quick creates the table and populates the cell values with the count of the column value for the intersecting row value. Typically, you choose a measure and two dimensions measurable by that measure. Pivot tables support scroll down and right. You can add up to 20 fields as rows and 20 fields as columns. Up to 500,000 records are supported. Using a pivot table, you can do the following: + Specify multiple measures to populate the cell values of the table, so that you can see a range of data + Cluster pivot table columns and rows to show values for subcategories grouped by related dimension + Sort values in pivot table rows or columns + Apply statistical functions + Add totals and subtotals to rows and columns + Use infinite scroll + Transpose fields used by rows and columns + Create custom total aggregations To easily transpose the fields used by the rows and columns of the pivot table, choose the orientation icon (![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/pivot-orientation.png)) near the top right of the visual. To see options for showing and hiding totals and subtotals, formatting the visual, or exporting data to a CSV file, choose the Menu items icon at top right. As with all visual types, you can add and remove fields. You can also change the field associated with a visual element, change field aggregation, and change date field granularity. In addition, you can focus on or exclude rows or columns. For more information about how to make these changes to a pivot table, see [Changing fields used by a visual in Amazon Quick](changing-visual-fields.md). For information on formatting pivot tables, see [Formatting in Amazon Quick](formatting-a-visual.md). For information on custom total aggregations for pivot tables, see [Custom total values](tables-pivot-tables-custom-totals.md). **Topics** + [ ## Pivot table features ](#pivot-table-features) + [ # Creating a pivot table ](create-pivot-table.md) + [ # Orienting pivot table values ](pivot-table-value-orientation.md) + [ # Expanding and collapsing pivot table clusters ](expanding-and-collapsing-clusters.md) + [ # Showing and hiding pivot table columns in Quick ](hiding-pivot-table-columns.md) + [ # Sorting pivot tables in Quick ](sorting-pivot-tables.md) + [ # Using table calculations in pivot tables ](working-with-calculations.md) + [ # Pivot table limitations ](pivot-table-limitations.md) + [ # Pivot table best practices ](pivot-table-best-practices.md) ## Pivot table features Pivot tables don't display a legend. To understand the features supported by pivot tables, use the following table. | Feature | Supported? | Comments | For more information | | --- | --- | --- | --- | | Changing the legend display | No | | [Legends on visual types in Quick](customizing-visual-legend.md) | | Changing the title display | Yes | | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Changing the axis range | Not applicable | | [Range and scale on visual types in Quick](changing-visual-scale-axis-range.md) | | Changing the visual colors | No | | [Colors in visual types in Quick](changing-visual-colors.md) | | Focusing on or excluding elements | Yes, with exceptions | You can focus on or exclude any column or row, except when you are using a date field as one of the dimensions. In that case, you can only focus on the column or row that uses the date dimension, not exclude it. | [Focusing on visual elements](focusing-on-visual-elements.md) [Excluding visual elements](excluding-visual-elements.md) | | Sorting | Yes | You can sort fields in the Rows or Columns field wells alphabetically or by a metric in ascending or descending order. | [Sorting visual data in Amazon Quick](sorting-visual-data.md) [Sorting pivot tables in Quick](sorting-pivot-tables.md) | | Performing field aggregation | Yes | You must apply aggregation to the field or fields you choose for the value. You can't apply aggregation to the fields that you choose for the rows or columns. If you choose to create a multi-measure pivot table, you can apply different types of aggregation to the different measures. For example, you can show the sum of the sales amount and the maximum discount amount. | [Changing field aggregation](changing-field-aggregation.md) | | Adding drill-downs | No | | [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md) | | Showing and hiding totals and subtotals | Yes | You can show or hide totals and subtotals for rows and columns. Metrics automatically roll up to show subtotals when you collapse a row or column. If you use a table calculation, use aggregates to display roll-ups. | | | Exporting or copying data | Yes | You can export all of the data to a CSV file. You can select and copy the content of the cells. | [Exporting data from visuals](exporting-data.md) | | Conditional formatting | Yes | You can add conditional formatting for values, subtotals and totals. | [Conditional formatting on visual types in Quick](conditional-formatting-for-visuals.md) | **Topics** # Creating a pivot table Use the following procedure to create a pivot table. **To create a pivot table** 1. On the analysis page, choose the **Visualize** icon on the tool bar. 1. On the **Visuals** pane, choose **\$1 Add**, and then choose the pivot table icon. 1. From the **Fields list** pane, choose the fields that you want to include. Amazon Quick automatically places these into the field wells. To change the placement of a field, drag it to the appropriate field wells. Typically, you use dimension or measure fields as indicated by the target field well. If you choose to use a dimension field as a measure, the **Count** aggregate function is automatically applied to it to create a numeric value. + To create a single-measure pivot table, drag a dimension to the **Rows** field well, a dimension to the **Columns** field well, and a measure to the **Values** field well. + To create a multi-measure pivot table, drag a dimension to the **Rows** field well, a dimension to the **Columns** field well, and two or more measures to the **Values** field well. + To create a clustered pivot table, drag one or more dimensions to the **Rows** field well, one or more dimensions to the **Columns** field well, and a measure to the **Values** field well. You can also select multiple fields for all of the pivot table field wells if you want to. Doing this combines the multi-measure and clustered pivot table approaches. **Note** To view roll-ups for calculated fields, make sure that you are using aggregates. For example, a calculated field with `field-1 / field-2 `doesn't display a summary when rolled up. However, `sum(field-1) / sum(field-2) `does display a roll-up summary. ## Choosing a layout When you create a pivot table in Amazon Quick, you can further customize the way your data is presented with Tabular and Hierarchy layout options. For pivot tables that use a tabular layout, each row field is displayed in its own column. For pivot tables that use a hierarchy layout, all row fields are displayed in a single column. Indentation is used to differentiate row headers of different fields. To change the layout of a pivot table visual, open the **Format visual** menu of the pivot table that you want to change and choose the layout option that you want from the **Pivot options** section. Depending on the layout that you choose for your pivot table visual, different formatting options are available. For more information about formatting differences between tabular and hierarchy pivot tables, see [Table and pivot table formatting options in Quick](format-tables-pivot-tables.md). # Orienting pivot table values Display orientation You can choose to display a pivot table in a columnar or row-based format. Columnar is the default. When you change to a row-based format, a column with the value name is added to the right of the row header column. **To change a pivot table format** 1. On the analysis page, choose the pivot table visual that you want to edit. 1. Expand the **Field wells** pane by choosing the field wells at the top of the visual. 1. On the **Values** field well, choose one of the following options: + Choose **Column** for a columnar format. + Choose **Row** for a row format. **Note** If you use only one metric, you can eliminate the repeated header by formatting the visual and styling it with the **Hide single metric** option. # Expanding and collapsing pivot table clusters If you are using grouped columns or rows in a pivot table, you can expand or collapse a group to show or hide its data in the visual. **To expand or collapse a pivot table group** 1. On the analysis page, choose the pivot table visual that you want to edit. 1. Choose one of the following: + To collapse a group, choose the collapse icon near the name of the field. + To expand a group, choose the expand icon near the name of the field. The collapse icon shows a minus sign. The expand icon shows a plus sign. In the following screenshot, `Customer Region` and the `Enterprise` segment are expanded, and `SMB` and `Startup` are collapsed. When a group is collapsed, its data is summarized in the row or column. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/pivot-table-collapse.png) # Showing and hiding pivot table columns in Quick Showing and hiding pivot table columns By default, all columns, rows, and their field values appear when you create a pivot table. You can hide columns and rows that you don't want to appear in the pivot table without changing the pivot table values. When you have more than one measure in the pivot table, you can also hide values. At any time, you can choose to show any hidden fields in the pivot table. When you publish the visual as part of a dashboard, anyone who subscribes to the dashboard can export the pivot table to a comma-separated value (CSV) or Microsoft Excel file. They can choose to export only the visible fields, or all fields. For more information, see [Exporting data from a dashboard to a CSV](export-or-print-dashboard.md#export-dashboard-to-csv). **To hide a column or row in a pivot table** 1. In your analysis, select the pivot table visual that you want to work with. 1. Choose the three-dot menu in the **Rows**, **Columns** or **Values** field wells, and then choose **Hide**. **To show all hidden fields in a pivot table** 1. In your analysis, select the pivot table visual that you want to work with. 1. Choose any field in the **Fields well** and choose **Show all hidden fields**. # Sorting pivot tables in Quick Sorting pivot tables In Amazon Quick, you can sort values in a pivot table by fields in the **Rows** and **Columns** field wells or quickly by column headers in the pivot table. In pivot tables, you can sort rows and columns independently of each other in alphabetical order, or by a measure. **Note** You can't run Total, Difference, and Percent Difference table calculations when a pivot table is being sorted by a measure. For more information about using table calculations in pivot tables, see [Using table calculations in pivot tables](working-with-calculations.md). ## Understanding sorting in pivot tables When you have multiple panes in a pivot table, sorting is applied to each pane independently. For example, the `Segment` column in the pivot table on the left is being sorted in ascending order by `Cost`. Given that there are multiple panes, the sort starts over for each pane and the rows within each pane (for `Segment`) are ordered by lowest to highest cost. The table on the right has the same sort applied, but the sort is being applied across the entire table, as shown following. ![\[Image of a pivot table with a sort highlighted in red.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/sorting-pivot-tables2.png) When you apply multiple sorts to a pivot table, sorting is applied from the outside dimension to the inside dimension. Consider the following example image of a pivot table. The `Customer Region` column is sorted by `Cost` in descending order (as shown in orange). The `Channel` column is sorted by Revenue Goal in ascending order (as shown in blue). ![\[Image of a pivot table showing two measure value columns sorted.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/sorting-pivot-tables3.png) ## Sorting pivot tables using row or column headers Sorting pivot tables using row or column headers Use the following procedure to sort a pivot table using Row or Column headers. **To sort values in a tabular pivot table using table headers** 1. In a tabular pivot table chart, choose the header that you want to sort. 1. For **Sort by**, choose a field to sort by and a sort order. You can sort dimension fields alphabetically a–z or z–a, or you can sort them by a measure in ascending or descending order. ![\[Animated .gif file of sorting values in a pivot table using column headers.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/sorting-pivot-table7.gif) ## Sorting pivot tables using value headers Sorting pivot tables using value headers Use the following procedure to sort a pivot table using value headers. **To sort a pivot table using value headers** 1. In a pivot table chart, choose the value header that you want to sort. 1. Choose **Ascending** or **Descending**. ![\[Animated .gif file of sorting values in a pivot table using value headers.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/sorting-pivot-tables-value.gif) Sorting by value headers in a pivot table also works on subtotals. ## Sorting tabular pivot tables using the field wells Sorting tabular pivot tables using the field wells Use the following procedure to sort values in a tabular pivot table using the field wells. **To sort values in a tabular pivot table using the field wells** 1. On the analysis page, choose the tabular pivot table that you want to sort. 1. Expand the **Field wells**. 1. In the **Rows** or **Columns** field well, choose the field that you want to sort, and then choose how you want to sort the field for **Sort by**. You can sort dimension fields in the **Rows** or **Columns** field wells alphabetically from a–z or z–a, or you can sort them by a measure in ascending or descending order. You also have the option to collapse all or expand all rows or columns for the field you choose in the field well. You can also remove the field, or to replace it with another field. + To sort a dimension field alphabetically, hover your cursor over the field in the **Rows** or **Columns** field well, and then choose the a–z or z–a sort icon. ![\[Image of a field in the Rows field well with the sort by field and alphabetical sort icons indicated in red squares.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/sorting-pivot-tables1.png) + To sort a dimension field by a measure, hover your cursor over the field in the **Rows** or **Columns** field well. Then choose a measure from the list, and then choose the ascending or descending sort icon. ![\[Image of a field in the Rows field well with the sort by field and sort icons indicated in red squares.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/sorting-pivot-tables4.png) Or, if you want more control over how the sort is applied to the pivot table, customize the sort options. **To create a sort using the **sort options**** 1. On the analysis page, choose the pivot table that you want to sort. 1. Expand **Field wells**. 1. Choose the field that you want to sort in the **Rows** or **Columns** field well, and then choose **Sort options**. 1. In the **Sort options** pane that opens at left, specify the following options: 1. For **Sort by**, choose a field from the drop-down list. 1. For **Aggregation**, choose an aggregation from the list. 1. For **Sort order**, select **Ascending** or **Descending**. 1. Choose **Apply**. ## Sorting hierarchy pivot tables using the field wells For tabular pivot tables, each field in the **Rows ** field well has a separate title cell. For hierarchy pivot tables, all row fields are displayed in a single column. To sort, collapse, and expand these row fields, select the **Rows** label to open the **Combined row fields** menu and choose the option that you want. Each field in a hierarchy pivot table can be individually sorted from the **Combined row fields** menu. ![\[Image of the Combined row fields menu.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/pivot-table-combined-row-fields-menu.png) More advanced formatting options such as **Hide** and **Remove** are available from the field well menus. # Using table calculations in pivot tables You can use table calculations to apply statistical functions to pivot table cells that contain measures (numeric values). Use the following sections to understand which functions you can use in calculations, and how to apply or remove them. The data type of the cell value automatically changes to work for your calculation. For example, say that you apply the **Rank** function to a currency data type. The values display as integers rather than currency, because rank isn't measured as currency. Similarly, if you apply the **Percent difference** function instead, the cell values display as percentages. **Topics** + [ # Adding and deleting pivot table calculations ](adding-a-calculation.md) + [ # Functions for pivot table calculations ](supported-functions.md) + [ # Ways to apply pivot table calculations ](supported-applications.md) # Adding and deleting pivot table calculations Use the following procedures to add, modify, and remove table calculation on a pivot table. **Topics** + [ # Adding a pivot table calculation ](add-a-calculation.md) + [ # Changing how a calculation is applied ](change-how-a-calculation-is-applied.md) + [ # Removing a calculation ](remove-a-calculation.md) # Adding a pivot table calculation Use the following procedure to add a table calculation to a pivot table. **To add a table calculation to a pivot table** 1. Expand the **Field wells** pane by choosing the field wells near the bottom of the visual. 1. Choose the field in the **Values** well that you want to apply a table calculation to, choose **Add table calculation**, and then choose the function to apply. **Note** You can't run Total, Difference, and Percent Difference table calculations when a pivot table is being sorted by a measure. To use these table calculations, remove the sort from the pivot table. # Changing how a calculation is applied Use the following procedure to change the way a table calculation is applied to a pivot table. **To change the way a table calculation is applied to a pivot table** 1. Expand the **Field wells** pane by choosing field wells at the top of the visual. 1. Choose the field in the **Values** well that has the table calculation that you want to change, choose **Calculate as**, and then choose the way that you want the calculation applied. # Removing a calculation Use the following procedure to remove a table calculation from a pivot table. **To remove a table calculation from a pivot table** 1. Expand the **Field wells** pane by choosing the field wells near the bottom of the visual. 1. Choose the field in the **Values** well that you want to remove the table calculation from, and then choose **Remove**. # Functions for pivot table calculations You can use the following functions in pivot table calculations. **Topics** + [ ## Running total ](#running-total) + [ ## Difference ](#difference) + [ ## Percentage difference ](#percent-difference) + [ ## Percent of total ](#percent-of-total) + [ ## Rank ](#rank) + [ ## Percentile ](#percentile) You can apply functions listed to the following data: ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/running-total1.png) ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/running-total1.png) ## Running total The **Running total** function calculates the sum of a given cell value and the values of all cells prior to it. This sum is calculated as `Cell1=Cell1, Cell2=Cell1+Cell2, Cell3=Cell1+Cell2+Cell3`, and so on. Applying the **Running total** function across the table rows, using **Table across** for **Calculate as**, gives you the following results. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/running-total2.png) ## Difference The **Difference** function calculates the difference between a cell value and value of the cell prior to it. This difference is calculated as `Cell1=Cell1-null, Cell2=Cell2-Cell1, Cell3=Cell3-Cell2,` and so on. Because `Cell1-null = null`, the Cell1 value is always empty. Applying the **Difference** function across the table rows, using **Table across** for **Calculate as**, gives you the following results. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/difference.png) ## Percentage difference The **Percentage Difference** function calculates the percent difference between a cell value and the value of the cell prior to it, divided by the value of the cell prior to it. This value is calculated as `Cell1=(Cell1-null)/null, Cell2=(Cell2-Cell1)/Cell1, Cell3=(Cell3-Cell2)/Cell2,` and so on. Because `(Cell1-null)/null = null`, the Cell1 value is always empty. Applying the **Percentage Difference** function across the table rows, using **Table across** for **Calculate as**, gives you the following results. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/percentage-difference.png) ## Percent of total The **Percent of Total** function calculates the percentage the given cell represents of the sum of all of the cells included in the calculation. This percentage is calculated as `Cell1=Cell1/(sum of all cells), Cell2=Cell2/(sum of all cells),` and so on. Applying the **Percent of Total** function across the table rows, using **Table across** for **Calculate as**, gives you the following results. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/percent-of-total.png) ## Rank The **Rank** function calculates the rank of the cell value compared to the values of the other cells included in the calculation. Rank always shows the highest value equal to 1 and lowest value equal to the count of cells included in the calculation. If there are two or more cells with equal values, they receive the same rank but are considered to take up their own spots in the ranking. Thus, the next highest value is pushed down in rank by the number of cells at the rank above it, minus one. For example, if you rank the values 5,3,3,4,3,2, their ranks are 1,3,3,2,3,6. For example, suppose that you have the following data. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/rank.png) Applying the **Rank** function across the table rows, using **Table across** for **Calculate as**, gives you the following results. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/rank2.png) ## Percentile The **Percentile** function calculates the percent of the values of the cells included in the calculation that are at or below the value for the given cell. This percent is calculated as follows. ``` percentile rank(x) = 100 * B / N Where: B = number of scores below x N = number of scores ``` Applying the **Percentile** function across the table rows, using **Table across** for **Calculate as**, gives you the following results. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/percentile.png) # Ways to apply pivot table calculations You can apply table calculations in the ways described following. Table calculations are applied to only one field at a time. Thus, if you have a pivot table with multiple values, calculations are only applied to the cells representing the field that you applied the calculation to. **Topics** + [ ## Table across ](#table-across) + [ ## Table down ](#table-down) + [ ## Table across down ](#table-across-down) + [ ## Table down across ](#table-down-across) + [ ## Group across ](#group-across) + [ ## Group down ](#group-down) + [ ## Group across down ](#group-across-down) + [ ## Group down across ](#group-down-across) ## Table across Using **Table across** applies the calculation across the rows of the pivot table, regardless of any grouping. This application is the default. For example, take the following pivot table. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/sample-pivot.png) Applying the **Running total** function using **Table across** gives you the following results, with row totals in the last column. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/table-across.png) ## Table down Using **Table down** applies the calculation down the columns of the pivot table, regardless of any grouping. Applying the **Running total** function using **Table down** gives you the following results, with column totals in the last row. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/table-down.png) ## Table across down Using **Table across down** applies the calculation across the rows of the pivot table, and then takes the results and reapplies the calculation down the columns of the pivot table. Applying the **Running total** function using **Table across down** gives you the following results. In this case, totals are summed both down and across, with the grand total in the lower-right cell. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/running-total-across-down.png) In this case, suppose that you apply the **Rank** function using **Table across down**. Doing so means that the initial ranks are determined across the table rows and then those ranks are in turn ranked down the columns. This approach gives you the following results. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/rank-table-across-down.png) ## Table down across Using **Table down across** applies the calculation down the columns of the pivot table. It then takes the results and reapplies the calculation across the rows of the pivot table. You can apply the **Running total** function using **Table down across** to get the following results. In this case, totals are summed both down and across, with the grand total in the lower-right cell. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/running-total-down-across.png) You can apply the **Rank** function using **Table down across** to get the following results. In this case, the initial ranks are determined down the table columns. Then those ranks are in turn ranked across the rows. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/rank-table-down-across.png) ## Group across Using **Group across** applies the calculation across the rows of the pivot table within group boundaries, as determined by the second level of grouping applied to the columns. For example, if you group by field-2 and then by field-1, grouping is applied at the field-2 level. If you group by field-3, field-2, and field-1, grouping is again applied at the field-2 level. When there is no grouping, **Group across** returns the same results as **Table across**. For example, take the following pivot table where columns are grouped by `Service Line` and then by `Consumption Channel`. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/sample-pivot.png) You can apply the **Running total** function using **Group across** to get the following results. In this case, the function is applied across the rows, bounded by the columns for each service category group. The `Mobile` columns display the total for both `Consumption Channel` values for the given `Service Line`, for the `Customer Region` and `Date` (year) represented by the given row. For example, the highlighted cell represents the total for the `APAC` region for `2012`, for all `Consumption Channel` values in the `Service Line` named `Billing`. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/group-across.png) ## Group down Using **Group down** applies the calculation down the columns of the pivot table within group boundaries, as determined by the second level of grouping applied to the rows. For example, if you group by field-2 and then by field-1, grouping is applied at the field-2 level. If you group by field-3, field-2, and field-1, grouping is again applied at the field-2 level. When there is no grouping, **Group down** returns the same results as **Table down**. For example, take the following pivot table where rows are grouped by `Customer Region` and then by `Date` (year). ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/sample-pivot.png) You can apply the **Running total** function using **Group down** to get the following results. In this case, the function is applied down the columns, bounded by the rows for each `Customer Region` group. The `2014` rows display the total for all years for the given `Customer Region`, for the `Service Line` and `Consumption Channel` represented by the given column. For example, the highlighted cell represents the total the `APAC` region, for the `Billing` service for the `Mobile` channel, for all the `Date` values (years) that display in the report. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/group-down.png) ## Group across down Using **Group across down** applies the calculation across the rows within group boundaries, as determined by the second level of grouping applied to the columns. Then the function takes the results and reapplies the calculation down the columns of the pivot table. It does so within group boundaries as determined by the second level of grouping applied to the rows. For example, if you group a row or column by field-2 and then by field-1, grouping is applied at the field-2 level. If you group by field-3, field-2, and field-1, grouping is again applied at the field-2 level. When there is no grouping, **Group across down** returns the same results as **Table across down**. For example, take the following pivot table where columns are grouped by `Service Line` and then by `Consumption Channel`. Rows are grouped by `Customer Region` and then by `Date` (year). ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/sample-pivot.png) You can apply the **Running total** function using **Group across down** to get the following results. In this case, totals are summed both down and across within the group boundaries. Here, these boundaries are `Service Line` for the columns and `Customer Region` for the rows. The grand total appears in the lower-right cell for the group. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/running-total-group-across-down.png) You can apply the **Rank** function using **Group across down** to get the following results. In this case, the function is first applied across the rows bounded by each `Service Line` group. The function is then applied again to the results of that first calculation, this time applied down the columns bounded by each `Customer Region` group. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/rank-group-across-down.png) ## Group down across Using **Group down across** applies a calculation down the columns within group boundaries, as determined by the second level of grouping applied to the rows. Then Amazon Quick takes the results and reapplies the calculation across the rows of the pivot table. Again, it reapplies the calculation within group boundaries as determined by the second level of grouping applied to the columns. For example, if you group a row or column by field-2 and then by field-1, grouping is applied at the field-2 level. If you group by field-3, field-2, and field-1, grouping is again applied at the field-2 level. When there is no grouping, **Group down across** returns the same results as **Table down across**. For example, take the following pivot table. Columns are grouped by `Service Line` and then by `Consumption Channel`. Rows are grouped by `Customer Region` and then by `Date` (year). ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/sample-pivot.png) You can apply the **Running total** function using **Group down across** to get the following results. In this case, totals are summed both down and across within the group boundaries. In this case, these are `Service Category` for the columns and `Customer Region` for the rows. The grand total is in the lower-right cell for the group. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/running-total-group-across-down.png) You can apply the **Rank** function using **Group down across** to get the following results. In this case, the function is first applied down the columns bounded by each `Customer Region` group. The function is then applied again to the results of that first calculation, this time applied across the rows bounded by each `Service Line` group. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/rank-group-down-across.png) # Pivot table limitations The following limitations apply to pivot tables: + You can create pivot tables with up to 500,000 records. + You can add any combination of row and column field values that add up to 40. For example, if you have 10 row field values, then you can add up to 30 column field values. + You can create pivot table calculations only on nonaggregated values. For example, if you create a calculated field that is a sum of a measure, you can't also add a pivot table calculation to it. + If you are sorting by a custom metric, you can't add a table calculation until you remove the custom metric sort. + If you are using a table calculation and then add a custom metric, you can't sort by the custom metric. + Totals and subtotals are blank for table calculations on metrics aggregated by distinct count. # Pivot table best practices It's best to deploy a minimal set of rows, columns, metrics, and table calculations, rather than offering all possible combinations in one pivot table. If you include too many, you risk overwhelming the viewer and you can also run into the computational limitations of the underlying database. To reduce the level of complexity and reduce the potential for errors, you can take the following actions: + Apply filters to reduce the data included in for the visual. + Use fewer fields in the **Row** and **Column** field wells. + Use as few fields as possible in the **Values** field well. + Create additional pivot tables so that each displays fewer metrics. In some cases, there's a business need to examine many metrics in relation to each other. In these cases, it can be better to use multiple visuals on the same dashboard, each showing a single metric. You can reduce the size of the visuals on the dashboard, and colocate them to form a grouping. If a decision the viewer makes based on one visual creates the need for a different view, you can deploy custom URL actions to launch another dashboard according to the choices made by the user. It's best to think of visuals as building blocks. Rather than using one visual for multiple purposes, use each visual to facilitate one aspect of a larger business decision. The viewer should have enough data to make a well-informed decision, without being overwhelmed by the inclusion of all possibilities. # Using radar charts Using radar charts You can use radar charts, which are also known as spider charts, to visualize multivariate data in Amazon Quick. In a radar chart, one or more groups of values are plotted over multiple common variables. Each variable has its own axis, and each axis is arranged radially around a central point. The data points from a single observation are plotted on each axis and connected to each other to form a polygon. Multiple observations can be plotted in a single radar chart to display multiple polygons, which makes it easier to spot outlying values for multiple observations quickly. In Quick, you can organize a radar chart along its category, value, or color axes by dragging and dropping fields to the **Category**, **Value**, and **Color** field wells. How you choose to distribute fields among the field wells determines the axis that the data is plotted on. The following image shows an example of a radar chart. ![\[Radar chart plotting employee satisfaction variables by department.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/radar-chart-example.png) ## Radar chart features To view the features supported by radar charts, use the following table. **** | Feature | Supported? | Comments | For more information | | --- | --- | --- | --- | | Changing the legend display | Yes | | [Legends on visual types in Quick](customizing-visual-legend.md) | | Changing the title display | Yes | | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Changing the axis range | Yes | | [Range and scale on visual types in Quick](changing-visual-scale-axis-range.md) | | Changing the visual colors | Yes | | [Colors in visual types in Quick](changing-visual-colors.md) | | Focusing on or excluding elements | Yes | | [Focusing on visual elements](focusing-on-visual-elements.md) [Excluding visual elements](excluding-visual-elements.md) | | Sorting | Limited | You can only sort data fields that are in the Category and Color field wells. | [Sorting visual data in Amazon Quick](sorting-visual-data.md) | | Performing field aggregation | Yes | | [Changing field aggregation](changing-field-aggregation.md) | | Adding drill-downs | Not supported | | [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md) | | Choosing size | Yes | | [Formatting in Amazon Quick](formatting-a-visual.md) | | Showing totals | Not supported | | [Formatting in Amazon Quick](formatting-a-visual.md) | ## Creating a radar chart Use the following procedure to create a radar chart. **To create a radar chart** 1. On the analysis page, choose **Visualize** on the tool bar. 1. Choose **Add** on the application bar, and then choose **Add visual**. 1. On the **Visual types** pane, choose the radar chart icon. 1. From the **Fields list** pane, drag the fields that you want to use to the appropriate field wells. In most cases, you want to use dimension or measure fields as indicated by the target field well. To create a radar chart, drag fields to the **Category**, **Value**, and **Group/Color** field wells. The axis that a radar chart is organized around is determined by the way that you organize fields into their respective field wells: + In a radar chart that uses a **value axis**, dimension values are shown as lines and axes represent value fields. To create a radar chart that uses a value axis, add one category field to the **Color** field well and one or more values to the **Value** field well. + In a radar chart that uses a **dimension axis**, group dimension values are shown as axes and value fields are shown as lines. All axes share a range and scale.To create a radar chart that uses a dimension axis, add one dimension to the **Group** field well and one or more values to the **Value** field well. + In a radar chart that uses a **dimension-color axis**, group dimension values are shown as axes and color dimension values are shown as lines. All axes share a range and scale. To create a radar chart that uses a dimension-color axis, add one dimension to the **Category** field well, one value to the **Value** field well, and one dimension to the **Color** field well. # Using Sankey diagrams Using Sankey diagrams Use Sankey diagrams to show flows from one category to another, or paths from one stage to the next. For example, a Sankey diagram can show the number of people migrating from one country to another. A Sankey diagram can also show the path a web visitor takes from one page to the next on a company website, with possible stops along the way. ## Data for Sankey diagrams To create Sankey diagrams in Quick, your dataset should contain a measure and two dimensions (one dimension containing source categories and another containing destination categories). The following table is a simple example of data for a Sankey diagram. | Dimension (Source) | Dimension (Destination) | Measure (Weight) | | --- | --- | --- | | A | W | 500 | | A | X | 23 | | A | Y | 147 | The following Sankey diagram is created when the dimensions and measure are added to the field well, with the A node on the left linking to the W, Y, and X nodes on the right. The width of each link between nodes is determined by the value in the Measure (Weight) column. The nodes are automatically ordered. To create multilevel Sankey diagrams in Amazon Quick, your dataset should still contain a measure and two dimensions (one for source and one for destination), but in this case your data values differ. The following table is a simple example of data for a multilevel Sankey diagram with two stages. | Dimension (Source) | Dimension (Destination) | Measure (Weight) | | --- | --- | --- | | A | W | 500 | | A | X | 23 | | A | Y | 147 | | W | Z | 300 | | X | Z | 5 | | Y | Z | 50 | The following Sankey diagram is created when the dimensions and measure are added to the field well. Here, the A node on the left links to the W, Y, and X nodes in the middle, and the W, Y, and X nodes then link to the Z node on the right. The width of each link between nodes is determined by the value in the Measure (Weight) column. ### Working with cyclical data Sometimes, the data that you use for a Sankey diagram contains cycles. For example, suppose that you're visualizing user traffic flows between pages on a website. You might discover that users who come to page A move to page E, and then come back to page A. An entire flow might look something like A-E-A-B-A-E-A. When your data contains cycles, the nodes in each cycle are repeated in Quick. For example, if your data contains the flow A-E-A-B-A-E-A, the following Sankey diagram is created. ## Preparing data for Sankey diagrams If your dataset doesn't contain Source or Destination columns, prepare your data to include them. You can prepare data when creating a new dataset, or when editing an existing dataset. For more information about creating a new dataset and preparing it, see [Creating datasets](creating-data-sets.md). For more information about opening an existing dataset for data preparation, see [Editing datasets](edit-a-data-set.md). The following procedure uses an example table (illustrated in following) to demonstrate how to prepare your data for Sankey diagrams in Quick. The table includes three columns: Customer ID, Time, and Action. | Customer ID | Time | Action | | --- | --- | --- | | 1 | 9:05 am | Step 1 | | 1 | 9:06 am | Step 2 | | 1 | 9:08 am | Step 3 | | 2 | 11:44 am | Step 1 | | 2 | 11:47 am | Step 2 | | 2 | 11:48 am | Step 3 | To create a Sankey diagram in Quick using this data, first add Source and Destination columns to the table. Use the following procedure to learn how. **To add Source and Destination columns to your table** 1. Add a Step Number column to the table to number or rank each row. There are multiple ways to compute the Step Number column. If your data source is compatible with SQL and your database supports `ROW_NUMBER` or `RANK` functions, you can use custom SQL in Quick to order the rows in the Step Number column. For more information about using custom SQL in Quick, see [Using SQL to customize data](adding-a-SQL-query.md). [\[See the AWS documentation website for more details\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/sankey-diagram.html) 1. Add a Next Row Number column to the table with values equal to Step Number plus one. For example, in the first data row of the table, the value for Step Number is 1. To compute the value for Next Step Number for that row, add 1 to that value. 1 \$1 1 = 2 The value for Step Number in the second data row of the table is 2; therefore, the value for Next Step Number is 3. 2 \$1 1 = 3 [\[See the AWS documentation website for more details\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/sankey-diagram.html) 1. Join the table with itself: 1. For **Join type**, choose **Inner**. 1. For **Join clauses**, do the following: 1. Choose **Customer ID** = **Customer ID** 1. Choose **Next Step Number** = **Step Number** Joining the two tables creates two columns for Customer ID, Time, Action, Step Number and Next Step Number. The columns from the table at the left of the join are Source columns. The columns from the table at the right of the join are Destination columns. For more information about joining data in Quick, see [Joining data](joining-data.md). 1. (Optional) Rename columns to indicate sources and destinations. The following is an example: 1. Rename the **Action** column on the left to **Source**. 1. Rename the **Action [copy]** column on the right to **Destination**. 1. Rename the **Time** column on the left to **Start Time**. 1. Rename the **Time [copy]** column on the right to **End Time**. Your data is now ready to visualize. ## Creating Sankey diagrams Use the following procedure to create a Sankey diagram. **To create a Sankey diagram** 1. On the analysis screen, choose **Visualize** on the left toolbar. 1. On the application bar, choose **Add**, and then choose **Add visual**. 1. On the **Visual types** pane, choose the Sankey diagram icon. 1. On the menu in the upper-right corner of the visual, choose the **Properties** icon. 1. In the **Properties pane**, choose either the **Source** or **Destination** section. ### Customizing the number of nodes Use the following procedure to customize the number of nodes that appear in a Sankey diagram. Quick supports up to 100 Source/Destination nodes. **To customize the number of nodes that appear in a Sankey diagram** 1. On the analysis page, choose the Sankey diagram visual that you want to format. 1. On the menu in the upper-right corner of the visual, select the **Format Visual** icon. 1. In the **Properties** pane that opens, choose either the **Source** or **Destination** tab. 1. For **Number of nodes displayed**, enter a number. The nodes in the diagram update to the number that you specified. The top nodes are automatically shown. All other nodes are placed in an **Other** category. **Note** Specifying the number of Source nodes controls how many Source nodes can appear overall in the diagram. Specifying the number of Destination nodes controls how many Destination nodes can appear per Source node. This means that if there is more than one Source node in your diagram, the overall number of Destination nodes will be higher than the number specified. Quick supports up to 100 Source/Destination nodes. For example, the following Sankey diagram has a limit of three source nodes (out of five), so the top three are shown in the diagram. The other two source nodes are placed in the Other category. To remove the **Other** category from the diagram, select it in the view and choose **Hide “other” categories**. ## Sankey diagram features To understand the features supported by Sankey diagrams, use the following table. | Feature | Supported? | For more information | | --- | --- | --- | | Changing the legend display | No | | | Changing the title display | Yes | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Changing the axis range | No | | | Changing the visual colors | No | | | Focusing on or excluding elements | Yes | [Focusing on visual elements](focusing-on-visual-elements.md) [Excluding visual elements](excluding-visual-elements.md) | | Sorting | No | | | Performing field aggregation | Yes | [Changing field aggregation](changing-field-aggregation.md) | | Adding drill-downs | No | | | Conditional formatting | No | | # Using scatter plots Use scatter plots to visualize two or three measures across two dimensions. Each bubble on the scatter plot represents one or two dimension values. The X and Y axes represent two different measures that apply to the dimension. A bubble appears on the chart at the point where the values for the two measures for an item in the dimension intersect. Optionally, you can also use bubble size to represent an additional measure. Scatter plots show up to 2500 datapoints in aggregated and unaggregated scenarios regardless of whether a color or label dimension is used in the visual. Due to the order of limit operations, there may be cases where fewer datapoints for a dataset are shown. For more information about how Amazon Quick handles data that falls outside display limits, see [Display limits](working-with-visual-types.md#display-limits). ## Scatter plot features To understand the features supported by scatter plots, use the following table. | Feature | Supported? | Comments | For more information | | --- | --- | --- | --- | | Changing the legend display | Yes, with exceptions | Scatter plots display a legend if you have the Group/Color field well populated. | [Legends on visual types in Quick](customizing-visual-legend.md) | | Changing the title display | Yes | | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Changing the axis range | Yes | You can set the range for both the X and Y axes. | [Range and scale on visual types in Quick](changing-visual-scale-axis-range.md) | | Showing or hiding axis lines, grid lines, axis labels, and axis sort icons | Yes | | [Axes and grid lines on visual types in Quick](showing-hiding-axis-grid-tick.md) | | Changing the visual colors | Yes | | [Colors in visual types in Quick](changing-visual-colors.md) | | Focusing on or excluding elements | Yes, with exceptions | You can focus on or exclude a bubble in a scatter plot, except when you are using a date field as a dimension. In that case, you can only focus on a bubble, not exclude it. | [Focusing on visual elements](focusing-on-visual-elements.md) [Excluding visual elements](excluding-visual-elements.md) | | Sorting | No | | [Sorting visual data in Amazon Quick](sorting-visual-data.md) | | Performing field aggregation | Yes | You must apply aggregation to the fields you choose for the X axis, Y axis, and size, and can't apply aggregation to the field that you choose for the group or color. | [Changing field aggregation](changing-field-aggregation.md) | | Displaying unaggregated fields | Yes | On the field context menu, choose None to display unaggregated X and Y axis values. If your scatter plot shows unaggregated fields, you can't apply aggregations to the field that is in the color or label field well. Mixed aggregation is not supported for scatter plots. | | | Adding drill-downs | Yes | You can add drill-down levels to the Group/Color field well. | [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md) | ## Creating a scatter plot Use the following procedure to create a scatter plot. **To create a scatter plot** 1. On the analysis page, choose **Visualize** on the tool bar. 1. Choose **Add** on the application bar, and then choose **Add visual**. 1. On the **Visual types** pane, choose the scatter plot icon. 1. From the **Fields list** pane, drag the fields that you want to use to the appropriate field wells. Typically, you want to use dimension or measure fields as indicated by the target field well. If you choose to use a dimension field as a measure, the **Count** aggregate function is automatically applied to it to create a numeric value. To create a scatter plot, drag a measure to the **X axis** field well, a measure to the **Y axis** field well, and a dimension to the **Color** or **Label** field well. To represent another measure with bubble size, drag that measure to the **Size** field well. 1. (Optional) Add drill-down layers by dragging one or more additional fields to the **Color** field well. For more information about adding drill-downs, see [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md). ## Scatter plot use cases You can choose to plot unaggregated values even if you are using a field on Color by using the aggregate option **none** on the field menu, which also contains aggregation options like **sum**, **min**, and **max**. If one value is set to be aggregated, the other value will be automatically set as aggregated. The same applies to unaggregated scenarios. Mixed aggregation scenarios are not supported, meaning that one value cannot be set as aggregated while the other is unaggregated. Note that the unaggregated scenario, which is the **none** option, is supported only for numerical values, while categorical values, such as dates or dimensions, will display only aggregate values, such as **count** and **count distinct**. Using the **none** option, you can choose to set both X and Y values to either aggregated or unaggregated from the **X axis** and **Y axis** field menus. This will define whether or not values will be aggregated by dimensions in the **Color** and **Label** field wells. To get started, add the required fields and choose the appropriate aggregation based on your use case,as shown in the following sections. ### Unaggregated use cases + Unaggregated X and Y values with Color ![\[unaggregated-color\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/unaggregated-color.png) + Unaggregated X and Y values with Label ![\[unaggregated-label\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/unaggregated-label.png) + Unaggregated X and Y values with Color and Label ![\[unaggregated-color-label\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/unaggregated-color-label.png) ### Aggregated use cases + Aggregated X and Y values with Color ![\[aaggregated-color\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/aggregated-color.png) + Aggregated X and Y values with Label ![\[aggregated-label\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/aggregated-label.png) + Aggregated X and Y values with Color and Label ![\[aggregated-color-label\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/aggregated-color-label.png) # Using tables as visuals Use a table visual to see a customized table view of your data. To create a table visual, choose at least one field of any data type. You can add as many columns as you need, up to 200. You can also add calculated columns. Table visuals don't display a legend. You can hide or display the title on a table. You can also hide or display totals, and choose to show totals at the top or the bottom of the table. For more information, see [Analytics formatting per type in Quick](analytics-format-options.md). **To create a table visual** 1. Open Amazon Quick and choose **Analyses** on the navigation pane at left. 1. Choose one of the following: + To create a new analysis, choose **New analysis** at upper right. For more information, see [Starting an analysis in Quick Sight](creating-an-analysis.md). + To use an existing analysis, choose the analysis that you want to edit. 1. Choose **Insert** from the file menu and then **Add Visual**. 1. At lower left, choose the table icon from **Visual types**. 1. On the **Fields** list pane, choose the fields that you want to use. If you want to add a calculated field, choose **Insert** on the file menu and then **Add Calculated Field**. To create a nonaggregated view of the data, add fields only to the **Value** field well. Doing this shows data without any aggregations. To create an aggregated view of the data, choose the fields that you want to aggregate by, and then add them to the **Group by** field well. **To show or hide columns on a table** 1. On your visual, choose the field that you want to hide, then choose **Hide column**. 1. To display hidden columns, choose any column, then choose **Show all hidden columns**. **To transpose columns to rows and rows to columns** + Choose the transpose icon ( ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/transpose-icon.png)) near the top right of the visual. It has two arrows at a 90 degree angle. **To vertically align columns** 1. On your visual, choose the **Format visual** icon ( ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/format-visual-icon.png)) near the top right of the visual. 1. In the **Properties** pane, choose **Table options**, and choose your table's vertical alignment. **To wrap the text for headers** 1. On your visual, choose the **Format visual** icon ( ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/format-visual-icon.png)) near the top right of the visual. 1. In the **Properties** pane, choose **Table options**, and select **Wrap header text**. **To rearrange columns in a table chart** 1. Open the analysis with the visual that you want to sort. Visuals pane will be open by default. 1. Do one of the following: + Drag and drop one or more fields in **Field wells** to rearrange their order. + Select a field directly in the table and choose the left or right arrow on **Move column**. # Using field styling You can render URLs in a table as links by using the **Field styling** pane of the format visual menu. You can add up to 500 rows of links for each page in a table. Only https and mailto hyperlinks are supported. **To add links to your tables** 1. From the Quick homepage, choose **Analyses**, and then choose the analysis that you want to customize. 1. Choose the table that you want to change. 1. On the menu at the upper right of the table, choose **Format visual**. 1. For **Format visual**, choose **Field styling**. 1. On the **Field styling** pane, choose the field that you want to style from the menu. 1. In the **Url options** section of the **Field styling** menu, choose **Make URLs hyperlinks**. After you add links to your table, you can choose where you want the links to open when they're selected in the **Open in** section of the **Field style** pane. You can choose to have links open in a new tab, a new window, or in the same tab. You can also choose how you want to style the link in the **Style as** section of **Field style** pane. Your links can appear as hyperlinks, icons, or plain text, or you can set a custom link. To adjust the font size of a link icon or URL, change the **Font size** in the **Cells** section of the **Table options** pane of the **Format visual** menu. You can set any URLs in your table that point to images to render in the table as images. Doing this can be useful when you want to include an image of a product as a part of a table. **To show URLs as images** 1. From the Quick home page, choose **Analyses**, and then choose the analysis that you want to customize. 1. Choose the table that you want to change. 1. On the menu at the upper-right of the table, choose **Format visual**. 1. In the **Format visual** menu, choose **Field styling**. 1. In the **Field styling** pane, choose the field that you want to style from the menu. 1. In the **Url options** section of the **Field styling** menu, choose **Show URLs as images**. After rendering images in a table, you can choose how to size the images in the **Image sizing** section of the **Field style** pane. You can fit images to their cell's height or width, or you can choose not to scale the image. Images fit to a cell's height by default. # Freeze columns to table visuals Freeze columns You can freeze columns to your table visuals to lock specific columns in place on screen. This allows essential information to remian visible while readers scroll across the table. You can freeze columns one at a time, or you can freeze groups of columns in one action. All pinned columns are fixed to the far left side of the table and stay visible on screen at all times. This allows Quick readers to have a constant reference point for key data or information as they interact with other parts of the table. **To freeze columns to a table** 1. On the table that you want to freeze a column to, choose the column that you want to pin. 1. Choose one of the following options. + To freeze a single column, choose **Freeze column**. + To freeze all columns up to the column that you choose, choose **Freeze up to this column**. If your table has multiple pinned columns, you can reorder the columns in the order that you want. To adjust the order of the pinned columns on a table, choose the header of the column that you want to move, and then choose **Move** in the direction that you want. **To unfreeze columns from a table** 1. On the table that you want to change, choose the pinned column that you wnat to unpin. 1. Choose one of the following options. + To unfreeze a single column, choose **Unfreeze column**. + To unfreeze all frozen columns, choose **Unfreeze all columns**. # Custom total values Quick authors can define the total and subtotal aggregations for their table or pivot table visuals from the field wells. For tables,the custom total menu is only available if totals are toggled on for the visual. **To change the aggregation of a total or subtotal** 1. Navigate to the analysis that you want to change, and choose the table or pivot table visual whose total you want to define. 1. Choose the field that you want to change from the field wells. 1. Choose **Total**, and then choose the aggregation that you want. The following options are available. + **Default** – The total calculation uses the same aggregation as the metric field. + **Sum** – Calculates the sum of the data in the visual. + **Average** – Calculates the average of the data in the visual. + **Min** – Calculates the minimum value of the data in the visual. + **Max** – Calculates the maximum value of the data in the visual. + **None (HIDE)** – Totals are not calculated. When you choose this option, the total and subtotal cells in the visual are left blank. If the outer dimension is sorted with the metric field that calculates the total or subtotal, the dimension is sorted alphabetically. When you change the value from **None (HIDE)** to another value, the outer dimension is sorted by the subtotals that are calculated with the specified aggregation type. The following limitations apply to custom totals. + Conditional formatting is not supported for custom totals. + Total aggregations aren't supported for string columns. Total aggregations include **Min**, **Max**, **Sum**, and **Average**. + Date columns are incompatible with **Average** and **Sum** total aggregation functions. # Sorting tables In Amazon Quick, you can sort values in a table by fields in the columns headers of the table or with the **Sort visual** tool. You can sort up to 10 columns in a single table. Quick can also use an off-visual sort You can sort columns in an **Ascending** or a **Descending** order. The following image shows the **Sort visual** icon and pop over. ![\[The Sort visual icon and the Sort visual pop over that it opens.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/table-sort-icon.png) ## Single column sort options Quick Authors can access single column sort options from the field wells, the column headers, or from the **Sort visual** menu. Use the procedure below to use set up a single column sort on a table in Quick. 1. Open the [Quick console](https://quicksight.aws.amazon.com/). 1. Open the analysis that you want to work in and navigate to the table that you want to sort. 1. Choose the header of the column that you want to sort. 1. For **Sort by**, choose the arrow icon, and then choose the field that you want to sort by. You can also set up a single column sort in the **Sort visual** menu. To access the sort visual menu, choose the **Sort visual** icon in the on-visual menu. In the **Sort visual** menu, choose the field that you want to sort by, and then choose if you want the sort in an ascending or descending order. By default, new sorts are sorted in an ascending order. When you are finished, choose **APPLY**. Tables that use single column sorting are sorted one column at a time. When a user chooses a new column to sort by, the previous sort order is overridden. To make changes to a single column sort, open the **Sort visual** menu annd use the dropdown menus to choose a new field or sort order. When you are finished with your changes, choose **APPLY**. To reset a table to its original state, open the **Sort visual** menu and choose **RESET**. ## Multi column sort options Quick authors can access multi column sort options from the **Sort visual** menu. Use the procedure below to set up a multi column sort for a table. 1. Open the [Quick console](https://quicksight.aws.amazon.com/). 1. Open the analysis that you want to work in and navigate to the table that you want to sort. 1. Choose the **Sort visual** icon to open the **Sort visual** menu. 1. Alternatively, choose a header that you want to sort. 1. For **Sort by**, choose the arrow icon, and then choose **Multiple fields**. 1. In the **Sort visual** menu that opens, choose a field from the **Sort by** dropdown, and then choose whether you want the field sorted in an ascending or descending order. 1. To add another sort, choose **ADD SORT**, and repeat the workflow from Step 4. You can add up to 10 sorts to each table. 1. When you are finished, choose **APPLY**. Columns are sorted in the order that they are added to the **Sort visual** menu. To change the order that columns are sorted by, open the **Sort visual** menu and use the **Sort by** dropdowns to reorder the sorts. When you are finished, choose **APPLY** to apply the new sort order to the table. To reset a table to its original state, open the **Sort visual** menu and choose **RESET**. ## Off visual sort options Quick authors can configure an off-visual sort to sort the values in a table by a field and aggregation that is a part of the dataset that the table uses but not in one of the table's field wells. One off-field sort can be configured to a single table at a time. Use the procedure below to configure an off-visual sort. **To add an off-visual sort to a table** 1. Open the [Quick console](https://quicksight.aws.amazon.com/). 1. Open the analysis that you want to work in and navigate to the table that you want to sort. 1. Choose the header of any column in the table. 1. For **Sort by**, choose the arrow icon, and then choose **Off-visual field**. 1. In the **Off-visual field** pane that appears, open the **Sort by** dropdown menu and choose the field that you want to sort. 1. For **Aggregation** open the dropdown menu and choose the aggregation that you want to use. 1. For **Sort order**, choose if you want the sort to be in an ascending or descending order. 1. When you are finished, choose **Apply**. After a off-visual sort is applied to a table, the sort is shown in the **Sort visual** menu. The sort order of a table that contains an off-visual sort depends on the sort configuration of the table when the off-visual sort is added. If an off-visual sort is added to a table that already has a single or multi column sort configured, the off-visual sort overrides all other sorts. If the off-visual sort is applied before single or multi column sorts, you can add and reorder more sorts to the table. # Using text boxes Add text to add context to sheets in an analysis by using a text box. Text can hold directions, descriptions, or even hyperlinks to external websites. The toolbar on the text box offers font settings so you can customize the font type, style, color, size, spacing, size in pixels, text highlights, and alignment. The text box itself has no format settings. To add text to a new text box, simply select it and begin typing. # Using tree maps To visualize one or two measures for a dimension, use tree maps. Each rectangle on the tree map represents one item in the dimension. Rectangle size represents the proportion of the value for the selected measure that the item represents compared to the whole for the dimension. You can optionally use rectangle color to represent another measure for the item. Rectangle color represents where the value for the item falls in the range for the measure, with darker colors indicating higher values and lighter colors indicating lower ones. Tree maps show up to 100 data points for the **Group by** field. For more information about how Amazon Quick handles data that falls outside display limits, see [Display limits](working-with-visual-types.md#display-limits). ## Tree map features To understand the features supported by tree maps, use the following table. **** | Feature | Supported? | Comments | For more information | | --- | --- | --- | --- | | Changing the legend display | Yes | | [Legends on visual types in Quick](customizing-visual-legend.md) | | Changing the title display | Yes | | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Changing the axis range | Not applicable | | [Range and scale on visual types in Quick](changing-visual-scale-axis-range.md) | | Changing the visual colors | No | | [Colors in visual types in Quick](changing-visual-colors.md) | | Focusing on or excluding elements | Yes, with exceptions | You can focus on or exclude a rectangle from a tree map, except when you are using a date field as the dimension. In that case, you can only focus on a rectangle, not exclude it. | [Focusing on visual elements](focusing-on-visual-elements.md) [Excluding visual elements](excluding-visual-elements.md) | | Sorting | No | Default sorting is in descending order by the measure in the Size column. | [Sorting visual data in Amazon Quick](sorting-visual-data.md) | | Performing field aggregation | Yes | You must apply aggregation to the fields you choose for size and color, and can't apply aggregation to the field that you choose to group by. | [Changing field aggregation](changing-field-aggregation.md) | | Adding drill-downs | Yes | You can add drill-down levels to the Group by field well. | [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md) | ## Creating a tree map Use the following procedure to create a tree map. **To create a tree map** 1. On the analysis page, choose **Visualize** on the tool bar. 1. Choose **Add** on the application bar, and then choose **Add visual**. 1. On the **Visual types** pane, choose the tree map icon. 1. From the **Fields list** pane, drag the fields that you want to use to the appropriate field wells. Typically, you want to use dimension or measure fields as indicated by the target field well. If you choose to use a dimension field as a measure, the **Count** aggregate function is automatically applied to it to create a numeric value. To create a tree map, drag a measure to the **Size** field well and a dimension to the **Group by** field well. Optionally, drag another measure to the **Color** field well. 1. (Optional) Add drill-down layers by dragging one or more additional fields to the **Group by** field well. For more information about adding drill-downs, see [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md). # Using waterfall charts Use a waterfall chart to visualize a sequential summation as values are added or subtracted. In a waterfall chart, the initial value goes through a (positive or negative) change, with each change represented as a bar. The final total is represented by the last bar. Waterfall charts are also known as *bridges* because the connectors between the bars bridge the bars together, showing that they visually belong to the same story. Waterfall charts are most commonly used to present financial data, because you can show change within one time period or from one time period to another. This way, you can visualize the different factors that have an impact your project cost. For example, you can use a waterfall chart to show gross sales to net income within the same month, or the difference in net income from last year to this year, and the factors that were responsible for this change. You can also use waterfall charts to present statistical data, for example how many new employees you hired and how many employees left your company within a year. The following screenshot shows a waterfall chart. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/waterfall-chart.png) **To create a basic waterfall chart visual** 1. Open Amazon Quick and choose **Analyses** on the navigation pane at left. 1. Choose one of the following: + To create a new analysis, choose **New analysis** at upper right. For more information, see [Starting an analysis in Quick Sight](creating-an-analysis.md). + To use an existing analysis, choose the analysis that you want to edit. 1. Choose **Add (\$1), Add Visual**. 1. At lower left, choose the waterfall chart icon from **Visual types**. 1. On the **Fields list** pane, choose the fields that you want to use for the appropriate field wells. Waterfall charts require one category or measure in **Value**. 1. (Optional) Add drill-down layers by dragging one or more additional fields to the **Group/Color** field well. For more information about adding drill-downs, see [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md). To understand the features supported by waterfall charts, see [Analytics formatting per type in Quick](analytics-format-options.md). For customization options, see [Formatting in Amazon Quick](formatting-a-visual.md). # Using word clouds As an engaging way to display how often a word is used in relation to other words in a dataset, use word clouds. The best use for this type of visual is to show word or phrase frequency. It can also make a fun addition to show trending items or actions. You can use a fixed dataset for creative purposes. For example, you might make one of team goals, motivational phrases, various translations of a specific word, or anything else that you want to draw attention to. Each word in a word cloud represents one or more values in a dimension. The size of the word represents the frequency of a value's occurrence in a selected dimension, in proportion to the occurrences of other values in the same dimension. Word clouds are best when precision isn't important and there aren't a large number of distinct values. The following screenshot shows an example of a word cloud. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/word-cloud.png) To create a word cloud, use one dimension in the **Group by** field well. Optionally, you can add a metric to the **Size** field well. Word clouds usually look better with 20–100 words or phrases, but the format settings offer a wide range of flexibility. If you choose too many words, they can become too small to be legible, depending on the size of your display. By default, word clouds display 100 distinct words. To show more, change the format setting for **Number of words**. Word clouds are limited to 500 unique values for **Group by**. To avoid displaying the word **Other**, format the visual to hide the **Other** category. For more information about how Amazon Quick handles data that falls outside display limits, see [Display limits](working-with-visual-types.md#display-limits). ## Word cloud features To understand the features supported by word clouds, see the following table. | Feature | Supported? | Comments | For more information | | --- | --- | --- | --- | | Changing the legend display | No | | [Legends on visual types in Quick](customizing-visual-legend.md) | | Changing the title display | Yes | | [Titles and subtitles on visual types in Quick](customizing-a-visual-title.md) | | Changing the axis range | Not applicable | | [Range and scale on visual types in Quick](changing-visual-scale-axis-range.md) | | Changing the visual colors | Yes | To change the color, choose a word and then choose a color. | [Colors in visual types in Quick](changing-visual-colors.md) | | Focusing on or excluding elements | Yes | | [Focusing on visual elements](focusing-on-visual-elements.md) [Excluding visual elements](excluding-visual-elements.md) | | Sorting | Yes | | [Sorting visual data in Amazon Quick](sorting-visual-data.md) | | Performing field aggregation | Yes | You can't apply aggregation to the field that you choose for Group by. You must apply an aggregation to the field that you choose for Size. | [Changing field aggregation](changing-field-aggregation.md) | | Adding drill-downs | Yes | You can add drill-down levels to the Group by field well. | [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md) | | Using format options | Yes | You can choose to allow vertical words, emphasize scale, use a fluid layout, use lowercase, and set the amount of padding between words. You can set the maximum string length for the word cloud (default is 40). You can also choose the number of words for the Group by field (default is 100; maximum is 500). | [Formatting in Amazon Quick](formatting-a-visual.md) | | Showing totals | No | | [Formatting in Amazon Quick](formatting-a-visual.md) | ## Creating a word cloud Use the following procedure to create a word cloud. **To create a word cloud** 1. On the analysis page, choose **Visualize** on the tool bar. 1. Choose **Add** on the application bar, and then choose **Add visual**. 1. On the **Visual types** pane, choose the word cloud icon. 1. From the **Fields list** pane, drag the fields that you want to use to the appropriate field wells. Typically, you want to use dimension or measure fields as indicated by the target field well. If you choose to use a dimension field as a measure, the **Count** aggregate function is applied by default. To create a word cloud, add a dimension to the **Group by** field well. Optionally, add a measure to the **Size** field well. 1. (Optional) Add drill-down layers by dragging one or more additional fields to the **Group by** field well. For more information about adding drill-downs, see [Adding drill-downs to visual data in Quick Sight](adding-drill-downs.md). # Formatting in Amazon Quick Formatting You choose from a variety of options to format and style your data visualizations. To format a visual, select the visual that you want to format and choose the **Format visual** icon on the upper-right corner of the visual. Once you have the format visual pane open, you can click on different visuals and controls to view formatting data for the specific visual or control. For more information about formatting a visual control, see [Using a control with a parameter in Amazon Quick](parameters-controls.md). Use the following sections to format and style your content: **Note** Any format changes applied from the field wells are applied only to the selected visual. **Topics** + [ # Analytics formatting per type in Quick ](analytics-format-options.md) + [ # Table and pivot table formatting options in Quick ](format-tables-pivot-tables.md) + [ # Adding data bars to tables in Quick ](format-data-bars.md) + [ # Adding sparklines to tables in Quick ](format-sparklines.md) + [ # Map and geospatial chart formatting options in Quick ](geospatial-formatting.md) + [ # Axes and grid lines on visual types in Quick ](showing-hiding-axis-grid-tick.md) + [ # Colors in visual types in Quick ](changing-visual-colors.md) + [ # Working with field level coloring in Amazon Quick ](format-field-colors.md) + [ # Conditional formatting on visual types in Quick ](conditional-formatting-for-visuals.md) + [ # KPI options ](KPI-options.md) + [ # Labels on visual types in Quick ](customizing-visual-labels.md) + [ # Formatting visual numeric data based on language settings in Quick ](customizing-visual-language-preferences.md) + [ # Legends on visual types in Quick ](customizing-visual-legend.md) + [ # Line and marker styling on line charts in Quick ](line-and-marker-styling.md) + [ # Missing data on visual types in Quick ](customizing-missing-data-controls.md) + [ # Reference lines on visuals types in Quick ](reference-lines.md) + [ # Formatting radar charts in Quick ](format-radar-chart.md) + [ # Range and scale on visual types in Quick ](changing-visual-scale-axis-range.md) + [ # Small multiples axis options ](small-multiples-options.md) + [ # Titles and subtitles on visual types in Quick ](customizing-a-visual-title.md) + [ # Tooltips on visual types in Quick ](customizing-visual-tooltips.md) # Analytics formatting per type in Quick Analytics formatting per type Use the following list to see what type of formatting works in a visualization during analysis: + Bar charts (both horizontal and vertical) support the following formatting: + Customize, display, or hide title, field labels, and data labels + Customize, display, or hide legend (exception: simple charts without clustering or multiple measures don't show a legend) + Specify axis range and steps on the x-axis for horizontal bar charts, and on the y-axis for vertical bar charts + Choose how many data points to display on the x-axis for vertical bar charts, and on the y-axis for horizontal bar charts + Show or hide axis lines, axis labels, axis sort icons, and chart grid lines + Customize, display, or remove reference lines + Show or hide the "other" category Horizontal bar charts support sorting on the y-axis and **Value**. Vertical bar charts support sorting on the x-axis and **Value**. Stacked bar charts support showing totals. + Box plots support the following formatting: + Customize, display, or hide title + Customize, display, or hide legend + Specify axis range and label tick on the x-axis and axis range and step on the y-axis + Show or hide axis lines, axis labels, axis sort icons, and chart grid lines + Choose how many data points to display on the y-axis. + Show or hide the “other” category + Add reference lines Box plots support sorting on **Group by**. + Combo charts support the following formatting: + Customize, display, or hide title, field labels, and data labels + Customize, display, or hide legend (exception: simple charts without clustering, stacking, or multiple measures don't show a legend) + Specify axis range on bars and lines + Synchronize the Y axes for both bars and lines into a single axis. + Choose how many data points to display on the x-axis + Show or hide axis lines, axis labels, axis sort icons, and chart grid lines + Customize, display, or remove reference lines + Show or hide the "other" category Combo charts support sorting on the x-axis, **Bars**, and **Lines**. + Donut charts support the following formatting: + Customize, display, or hide title, data labels, and legend + Customize, display, or hide the labels for group or color and value fields + Choose how many slices to display from **Group/Color** + Show or hide the "other" category Donut charts support sorting on **Group/Color **and **Value**. + Filled maps support the following formatting: + Customize, display, or hide title. + Customize, display, or hide the legend Filled maps support sorting on **Location **and **Color**. + Funnel charts support the following formatting: + Customize, display, or hide title, and data labels + Customize, display, or hide the labels for group or color and value fields + Choose how many stages to display in the **Group by** field + Show or hide the "other" category Funnel charts support sorting on **Group by** and **Value**. + Gauge charts support the following formatting: + Customize, display, or hide title. Display or hide axis labels. + Customize how to display the value or values: hidden, actual value, comparison + Choose the comparison method (available when you use two measures) + Choose the axis range and padding to display in the gauge chart + Choose the arc style (degrees from 180 to 360) and arc thickness Gauge charts don't support sorting. + Geospatial charts (maps) support the following formatting: + Customize, display, or hide title and legend + Choose the base map image. + Choose to display map points with or without clustering. Geospatial charts don't support sorting. + Heat maps support the following formatting: + Customize, display, or hide title, legend, and labels + Choose how many rows and columns to display + Choose colors or gradients. + Show or hide the "other" category Heat maps support sorting on **Values** and **Columns**. + Histogram charts support the following formatting: + Customize, display, or hide title, field labels, and data labels + Specify axis range, scale, and steps on the y-axis + Choose how many data points to display on the x-axis + Show or hide axis lines, axis labels, axis sort icons, and chart grid lines Histogram charts don't support sorting. + Key performance indicators (KPIs) support the following formatting: + Customize, display, or hide title + Display or hide trend arrows and progress bar + Customize comparison method as auto, difference, percent (%), or difference as percent (%) + Customize primary value displayed to be comparison or actual + Conditional formatting KPIs don't support sorting. + Line charts support the following formatting: + Customize, display, or hide title, field labels, and data labels + Customize, display, or hide legend (exception: simple charts don't show a legend) + Specify axis range and steps (on y-axis) + Choose how many data points to display on the x-axis + Show or hide axis lines, axis labels, axis sort icons, and chart grid lines + Customize, display, or remove reference lines + Customize the styling of lines and the markers for data points on a line + Show or hide the "other" category, except when the x-axis is a date Line charts support sorting on the x-axis and ** Value** for numeric purposes only. + Pie charts support the following formatting: + Customize, display, or hide title, data labels, and legend + Customize, display, or hide the labels for group or color and value fields + Show metrics as values, percentages, or both + Choose how many slices to display from the **Group/Color** field + Show or hide the "other" category Pie charts support sorting on **Value** and **Group/Color**. + Pivot tables support the following formatting: + Customize, display, or hide title + Customize, display, or hide the labels for column, row, and value fields + Customize the font sizes for table headers and cells/body + Display or hide totals and subtotals on rows or columns + Custom labels for totals or subtotals + Choose additional styling options: fit table to view, hide \$1/- buttons, hide column field names, hide duplicate label when using single metric + Conditional formatting Pivot tables support sorting on **Column** and **Row**. For more information on sorting pivot table data, see [Sorting pivot tables in Quick](sorting-pivot-tables.md). + Scatter plots support the following formatting: + Customize, display, or hide title, legend, field labels, and data labels + Customize, display, or remove reference lines + Specify axis range (on x-axis and y-axis) + Show or hide axis lines, axis labels, axis sort icons, and chart grid lines Scatter plots don't support sorting. + Tables support the following formatting: + Customize, display, or hide title, legend, and columns + Customize, display, or hide the column names for group-by and value fields + Customize the font sizes for table headers and cells/body + Display or hide totals at the top or bottom of the table + Provide a custom label for totals + Add conditional formatting Tables support sorting on **Group by** and **Value**. + Tree maps support the following formatting: + Customize, display, or hide title and legend + Customize, display, or hide the labels for group-by, size, and color fields + Choose colors or gradients. + Choose how many squares to display from the **Group by** field + Show or hide the "other" category Line charts support sorting on **Size**, **Group by** and **Color**. + Waterfall charts support the following formatting: + Customize, display, or hide title or subtitle + Customize the total label + Specify x-axis label size and orientation and y-axis label range and orientation. + Show or hide axis lines, axis labels, axis sort icons, and chart grid lines + Show or hide the "other" category + Customize the legend size and position. + Customize and display or hide data labels. Waterfall charts support sorting on **Category** and **Value**. + Word clouds support the following formatting: + Customize, display, or hide title + Customize the word color, and the number of words to display from the **Group by** field + Show or hide the "other" category + Choose additional styling options: allow vertical words, emphasize scale, or work with fluid layout, lowercase, padding level, or maximum string length Word clouds support sorting on **Group by**. # Table and pivot table formatting options in Quick Table and pivot table options You can customize tables and pivot tables in Quick to meet your business needs. You can customize table headers, cells, and totals by specifying the color, size, wrap, and alignment of text in each. You can also specify the height of rows in a table, add borders and grid lines, and add custom background colors. In addition, you can customize how to display totals and subtotals. If you have applied conditional formatting to a table or pivot table, it takes precedence over any other styling you configure. When you export table or pivot table visuals to Microsoft Excel, the formatting customizations that you applied to the visual aren't reflected in the downloaded Excel file. **To format a table or pivot table** + In your analysis, choose the table or pivot table that you want to customize, and then choose the **Format visual** icon. ![\[Image of the Format visual icon.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/format-tables-icon.png) The **Properties** pane opens at left. Following, you can find descriptions for options for customizing each area of your table or pivot table in the **Properties** pane. **Topics** + [ # Headers ](format-tables-headers.md) + [ # Cell formatting ](format-tables-pivot-tables-cells.md) + [ # Totals and subtotals ](format-tables-pivot-tables-totals.md) + [ # Row and column size in tables and pivot tables in Quick ](format-tables-pivot-tables-resize-rows-columns.md) + [ # Customize pivot table data ](format-tables-pivot-tables-layout-options.md) # Headers Headers ## Expand all headers Expand headers You can choose to expand all headers in a pivot table to show all child and grandchild rows of a header. **To expand all headers of a pivot table** 1. On the visual that you want to change, select any header to open the **On-visual** menu. 1. Choose **Expand all below**. ## Header height Header height You can customize table header height. **To customize the height of headers in a table** 1. In the **Properties** pane, choose **Headers**. 1. For **Row height**, enter a number in pixels. You can enter a whole number from 8 through 500. **To customize the height of headers in a pivot table** 1. In the **Properties** pane, choose **Headers**. 1. In the **Columns** section, for **Row height**, enter a number in pixels. You can enter a whole number from 8 through 500. ## Header text Header text You can customize table header text. **To customize header text in a table** 1. In the **Properties** pane, choose **Headers**. 1. Navigate to the **TEXT** section and do one or more of the following: + To change the color of the header text, choose the color swatch underneath **Text styling**, and then choose the color that you want the table text to be. + To change the font or font size of the header text, open the **Font** or **Font size** dropdown and choose the font or font size that you want. + To bold, italicize, or underline the header text, choose the appropriate icon from the style bar. + To wrap text in headers that are too long to fit, select **Wrap text**. Wrapping text in a header doesn't automatically increase the height of the header. Follow the previous procedure for increasing header height. + To change the horizontal alignment of text in the header, choose a horizontal alignment icon. You can choose left alignment, center alignment, right alignment, or automatic alignment. + To change the vertical alignment of text in the header, choose a vertical alignment icon. You can choose top alignment, middle alignment, or bottom alignment. **To customize header text in a pivot table** 1. In the **Properties** pane, choose **Headers**. The Headers section expands to show options for customizing column and row headers. 1. In the **Headers** section, do one or more of the following: + To apply row styling to field names of the rows or columns, choose **Style rows label** or **Style columns label** depending on the label that you want to customize. + To customize the header font, navigate to the **TEXT** subsection of the **Rows** or **Columns** section and do one or more of the following: + To change the color of the header text, choose the color swatch underneath **Text styling**, and then choose the color that you want the table text to be. + To change the font or font size of the header text, open the **Font** or **Font size** dropdown and choose the font or font size that you want. + To bold, italicize, or underline the header text, choose the appropriate icon from the style bar. + To change the horizontal alignment of text in the header, choose an alignment icon. You can choose left alignment, center alignment, right alignment, or automatic alignment. You can choose a horizontal alignment for column headers in the **Columns** section, and for row headers in the **Rows** section. + To change the vertical alignment of text in the header, choose an alignment icon. You can choose top alignment, middle alignment, or bottom alignment. You can choose a vertical alignment for column headers in the **Columns** section, and row headers in the **Rows** section. + To hide the rows label or column field names, choose the eye icon next to **Rows label** or **Column field names**. ## Header background color Header background color You can customize table headers' background color. **To customize the background color of table headers** 1. In the **Properties** pane, choose **Headers**. 1. For **Background**, choose the background color icon, and then choose a color. You can choose one of the provided colors, reset the header text color to the default color, or create a custom color. **To customize the background color of pivot table headers** 1. In the **Properties** pane, choose **Headers**. The **Headers** section expands to show options for customizing column and row headers. 1. In the **Columns** section, choose the background color icon, and then choose a color. 1. In the **Rows** section, choose the background color icon, and then choose a color. ## Header borders Header borders You can customize header borders' color. **To customize header borders in a table** 1. In the **Properties** pane, choose **Headers**. 1. For **Borders**, do one or more of the following: + To customize the type of border that you want, choose a border type icon. You can choose no borders, horizontal borders only, vertical borders only, or all borders. + To customize the border thickness, choose a border thickness. + To customize the border color, choose the border color icon, and then choose a color. You can choose one of the provided colors, reset the border color to the default color, or create a custom color. **To customize header borders in a pivot table** 1. In the **Properties** pane, choose **Headers**. The **Headers** section expands to show options for customizing column and row headers. 1. In the **Columns** and **Rows** sections, for **Borders**, do one or more of the following: + To customize the type of border that you want, choose a border type icon. You can choose no borders, horizontal borders only, vertical borders only, or all borders. + To customize the border thickness, choose a border thickness. + To customize the border color, choose the border color icon, and then choose a color. You can choose one of the provided colors, reset the border color to the default color, or create a custom color. ## Header styling options for hierarchy pivot tables You can hide or rename the **Rows** label of a hierarchy pivot table. **To make changes to the **Rows** label of a hierarchy pivot table** 1. Select the hierarchy pivot table that you want to change and open the **Format visual** menu. 1. In the **Headers** section, you can perform the following tasks + Choose **Hide rows label** to hide the **Rows** label from your pivot table. + For **Rows label**, enter the label that you want displayed on the pivot table. # Cell formatting Cell formatting ## Row height Row height You can customize table row height. **To customize the height of rows in a table or pivot table** 1. In the **Properties** pane, choose **Cells**. The **Cells** section expands to show options for customizing cells. 1. For **Row height**, enter a number in pixels. You can enter a whole number from 8 through 500. ## Cell text Cell text You can customize the formatting for cell text within a table. **To format the cell text in a table or pivot table** 1. In the **Properties** pane, choose **Cells**. The **Cells** section expands to show options for customizing cells. 1. For **Text**, do one or more of the following: + To change the color of the cell text, choose the color swatch underneath **Text styling**, and then choose the color that you want the table text to be. + To change the font or font size of the cell text, open the **Font** or **Font size** dropdown and choose the font or font size that you want. + To bold, italicize, or underline the cell text, choose the appropriate icon from the style bar. + To wrap text in headers that are too long to fit, select **Wrap text**. Wrapping text in cells doesn't automatically increase the row height. Follow the previous procedure for increasing row height. + To change the horizontal alignment of text in cells, choose a horizontal alignment icon. You can choose left alignment, center alignment, right alignment, or automatic alignment. Horizontal alignment can only be configured for the **Rows** fields of a hierarchy pivot table. + To change the vertical alignment of text in cells, choose a vertical alignment icon. You can choose top alignment, middle alignment, bottom alignment, or automatic. For tabular pivot tables, the value for **Automatic** is vertical. For hierarchy pivot tables, the value for **Automatic** is middle. ![\[Vertical and horizontal cell alignment options in the Format visual menu.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/format-pivot-table-alignment.png) ## Cell background color Cell background color You can customize table cells' background color. **To customize the background color of cells in a table or pivot table** 1. In the **Properties** pane, choose **Cells**. The **Cells** section expands to show options for customizing cells. 1. For **Background**, do one or more of the following: + To alternate background colors between rows, select **Alternate row colors**. Clearing this option means that all cells have the same background color. + If you choose to alternate background colors between rows, choose a color for **Odd rows** and a color for **Even rows** by choosing the background color icon for each and selecting a color. You can choose one of the provided colors, reset the background color to the default color, or create a custom color. + If you choose not to alternate background colors between rows, choose the background color icon and select a color for all cells. You can choose one of the provided colors, reset the background color to the default color, or create a custom color. ## Cell borders Cell borders You can customize table cells' borders. **To customize the borders for cells in a table or pivot table** 1. In the **Properties** pane, choose **Cells**. The **Cells** section expands to show options for customizing cells. 1. For **Borders**, do one or more of the following: + To customize the type of border that you want, choose a border type icon. You can choose no borders, horizontal borders only, vertical borders only, or all borders. + To customize the border thickness, choose a border thickness. + To customize the border color, choose the border color icon, and then choose a color. You can choose one of the provided colors, reset the border color to the default color, or create a custom color. # Totals and subtotals Totals and subtotals On tables and pivot tables, you can configure the display of totals or subtotals. Tables can display totals at the top or the bottom of the visual. Pivot tables can display totals and subtotals on rows and columns. ## Add totals and subtotals to tables and pivot tables in Quick Position totals and subtotals You can add total columns to your table and pivot table visuals. You can also add subtotal columns to your pivot table visuals. **To display or hide totals and subtotals for a pivot table** 1. To display totals, open the **Properties** pane and choose **Total**. + To show totals for rows, toggle the **ROWS** switch on. Totals are displayed on the bottom row of the visual. Choose **Pin totals** to keep the totals visible as you scroll through the table. + To show totals for columns, toggle the **COLUMNS** switch on. Totals are displayed on the last column of the visual. 1. To display totals, open the **Properties** pane and choose **Subtotal**. + To show subtotals for rows, toggle the **ROWS** switch on. Totals are displayed on the bottom row of the visual. + To show subtotals for columns, toggle the **COLUMNS** switch on. + For **Level**, choose one of the following: + Choose **Last** to only show the subtotal of the last field in the chart's hierarchy. This is the default option. + Choose **All** to show subtotals for every field. + Choose **Custom** to customize which fields show subtotals. After you add row totals to your table or pivot table visual, you can also choose to position the totals at the top or bottom of the visual. You can also change the position of column totals in pivot tables. **To position row or column totals in a table or pivot table** 1. In the **Properties** pane, choose **Total**. 1. (Optional) For **Rows**, choose **Show totals**. 1. (Optional) For **Columns**, choose **Show totals**. 1. (Optional) In the **Rows** menu, open the **Position** dropdown and choose the position that you want the totals to be displayed. Choose **Top** to position totals at the top of the table, or **Bottom** to position totals at the bottom of the table. 1. (Optional) In the **Columns** menu, open the **Position** dropdown and choose the position that you want the totals to be displayed. Choose **Left** to position totals at the left of the table, or **Right** to position totals at the right of the table. You can't change the position of the subtotals of a pivot table visual. If your pivot table uses a hierarchy layout, the subtotal rows are positioned at the top of the table. Tabular pivot table subtotals are displayed at the bottom of the table. ## Customize labels for totals and subtotals Customize labels You can rename the totals in table and pivot table visuals to provide better context for account readers. By default, the totals and subtotals appear without a label. **To rename totals in a table or pivot table visual** 1. In the **Properties** pane, choose **Total** or **Subtotal**. 1. For **Label**, enter a word or short phrase that you want displayed for the total. In pivot tables, you can also add labels to column totals and subtotals. To do so, enter a word or short phrase for **Label** in the **Columns** section. 1. (Optional) For tabular pivot tables, you can also add group names to subtotals. To add a group name to row subtotals, choose the **Plus (\$1)** icon next to the **Label** field to add the group name parameter that you want. You can also enter a word or short phrase to this field. You can also make changes to the text size and font color of the total and subtotal labels of your table and pivot table visuals. **To format totals and subtotals text** 1. In the **Properties** pane, choose **Total** or **Subtotal**. 1. For **Text**, do one or more of the following. + To change the color of the total or subtotal text, choose the color swatch underneath **Text styling**, and then choose the color that you want the table text to be. + To change the font or font size of the total or subtotal text, open the **Font** or **Font size** dropdown and choose the font or font size that you want. + To bold, italicize, or underline the total or subtotal text, choose the appropriate icon from the style bar. In pivot tables, you can also add format text for column totals and subtotals. To do so, repeat the above steps in the **Columns** section. ## Totals and subtotals background color Background color **To customize the background color for totals and subtotals** 1. In the **Properties** pane, choose **Total** or **Subtotal**. 1. For **Background**, choose the background color icon, and then choose a color. You can choose one of the provided colors, reset the background color to the default color, or create a custom color. In pivot tables, you can also add background colors for column totals and subtotals. To do so, choose a the background color icon for **Background** in the **Columns** section. ## Totals and subtotals borders Borders **To customize the borders for totals and subtotals** 1. In the **Properties** pane, choose **Total** or **Subtotal**. 1. For **Borders**, do one or more of the following: + To customize the type of border that you want, choose a border type icon. You can choose no borders, horizontal borders only, vertical borders only, or all borders. + To customize the border thickness, choose a border thickness. + To customize the border color, choose the border color icon, and then choose a color. You can choose one of the provided colors, reset the border color to the default color, or create a custom color. In pivot tables, you can also add borders for column totals and subtotals. To do so, repeat the above steps in the **Columns** section. ## Applying totals and subtotals styling to cells Apply styling In pivot tables, you can apply any text, background color, and border styling you apply to totals to cells in that same column or row. Row subtotals appear differently depending on the layout that your pivot table uses. For tabular pivot tables, explicit subtotal headers appear on the visual. For hierarchy pivot tables, explicit subtotal headers do not appear. Instead, authors apply subtotal styling to individual fields from the **Format visual** menu. Collapsed headers cannot be styled as subtotals. **To apply totals and subtotals styling to cells** 1. In the **Properties** pane, choose **Total** or **Subtotal**. 1. For **Apply styling to**, choose the visual that you want to apply subtotal styling to. You can choose from the following options. + **None**– Removes styling options from all cells. + **Headers only**– Aplies styling options to all headers in the pivot table. + **Cells only**– Applies styling options to all cells that aren't headers in the pivot table. + **Headers and cells**– Applies styling options to all cells in the pivot table. # Row and column size in tables and pivot tables in Quick Row and column size Authors and readers can resize rows and columns in a table or pivot table visual. They can adjust both row height and column width. Authors can also set the default column width for columns in a pivot table visual. **To resize a row in a table or pivot table** + In the table or pivot table visual, hover your cursor over the line that you want to resize until you see the horizontal cursor appear. When it appears, select the line and drag it to a new height. You can adjust the row height by selecting the horizontal lines on cells and row headers. ![\[Resize a row in a table or pivot table.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/resize-table-row1.gif) **To resize a column width in a table or pivot table** + In the table or pivot table visual, hover your cursor over the line that you want to resize until you see the vertical cursor appear. When it appears, select the line and drag it to a new width. You can adjust the column width by selecting the vertical lines on cells, column headers, and row headers. ![\[Resize a column in a table or pivot table.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/resize-table-row2.gif) **To set the default column width for columns in a pivot table** 1. Select the pivot table that you want to change and open the **Format visual** menu. 1. In the **Pivot options** section, navigate to the **Value column width (pixels)** field and enter the default value that you want in pixels. # Customize pivot table data Customize pivot table data You can customize how Quick readers view pivot tables so that they are easier to read and understand at a glance. You can choose to hide a pivot table's plus and minus icons, hide columns that only have a single-metric value, and hide collapsed columns from view. These options can help Quick authors remove clutter from their pivot tables and provide an easier reader experience for Quick users. This is not the same as choosing a pivot table layout. For more information on pivot table layout options, see [Choosing a layout](create-pivot-table.md#pivot-table-layout). These options can also be accessed from the **Combined row fields menu** of a pivot table. The layout that you choose for your pivot table determines how this menu is accessed. For more information on accessing the **Combined row fields** menu, see . **To make changes to a pivot table's layout** 1. In the **Format visual pane**, choose **Pivot options**. 1. In the **Pivot options** menu, select the following options to customize the view: + **Hide \$1/– buttons** – Hide the plus and minus icons from your pivot table by default. Readers can still choose to show the plus and minus icons and expand or collapse columns and rows. + **Hide single metric** – Hide columns that only have a single metric value. + **Hide collapsed columns** – Automatically hide all collapsed columns in a pivot table. This option is only available for tabular pivot tables. # Adding data bars to tables in Quick Data bars You can use data bars to add visual context to your table visuals in Amazon Quick. By injecting color into your tables, data bars can make it easier to visualize and compare data in a range of fields. *Data bars* are bars of different colors or shades that you add to the cells of a table. The bars are measured relative to the range of all cells in a single column, which is similar to a bar chart. You can use data bars to highlight a fluctuating trend, such as profit per quarter during the year. You can only apply data bars to fields that are added to the **Values** field well of the visual. You can't apply data bars to items that are added to group bys. You can create up to 200 different data bar configurations for a single table. ![\[An image that shows data bars in a table.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/data-bars-1.png) **To add data bars to a table** 1. On the analysis page, choose the visual that you want to format. 1. On the menu in the upper-right corner of the visual, select the **Format visual** icon. The** Format visual** pane opens. 1. In the **Properties** pane, open the **Visuals** dropdown list and choose **ADD DATA BARS**. 1. In the **Data bars** popup that appears, choose the value field that you want represented by the data bars. You can only choose from fields that are added to the **Values** field well of the visual. 1. (Optional) Choose the icon labeled **Positive color** to select the color that you want to represent positive value data bars. The default color is green. 1. (Optional) Choose the icon labeled **Negative color** to select the color that you want to represent negative value data bars. The default color is red. When you create data bars, they are named for the field values that they are representing. For example, if you add data bars to represent the profit of a product over time, the data bar configuration is labeled "Profit". In the **Visuals** pane of the **Properties** menu, data bars are listed in the order that they are created. **To remove data bars from a visual** 1. On the menu in the upper-right corner of the visual, select the **Format visual** icon. The **Properties** pane opens. 1. In the **Properties** pane, open the **Visuals** dropdown list and choose the data bar that you want to remove. 1. Choose **REMOVE DATA BARS**. # Adding sparklines to tables in Quick Sparklines Sparklines are small inline charts that display trends directly within table cells, helping readers quickly identify patterns and seasonality without leaving the table view. Use sparklines when you need compact trend visualization alongside your tabular data. **To apply sparklines to a table** 1. On the analysis page, choose the table visual that you want to format. 1. On the menu in the upper-right corner of the visual, select the **Format visual** icon. The **Format visual** pane opens. 1. In the **Properties** pane, open the **Visuals** dropdown list and choose **APPLY SPARKLINES**. 1. In the sparklines editing pane, configure the data settings: + For **Value column**, choose the measure field that you want the sparkline to represent. Fields already used by another sparkline or data bar are not available. + For **X-axis field**, choose the dimension field to plot along the horizontal axis. The X-axis field must not be the same as a field in the **Group by** field well. You can also configure the sort direction and time granularity (for date/time fields) of the X-axis field. 1. (Optional) Expand the **Presentation** section to customize the sparkline appearance. See [Sparkline options](#format-sparklines-options) for details. 1. (Optional) Configure marker visibility. All markers are hidden by default. You can choose to show: + **All points** – Show a marker on every data point. + **Max value** – Show a marker on the highest value. + **Min value** – Show a marker on the lowest value. 1. Choose **Apply**. The sparkline is named after the value field it represents (for example, "Profit"). Sparklines appear in the **Visuals** pane in the order they are created. ## Sparkline options The following table describes the sparkline presentation options. | Setting | Options | Default | Description | | --- | --- | --- | --- | | Y-axis behavior | Shared, Independent | Shared | Shared uses the same Y-axis scale across all rows for easy comparison. Independent scales each row separately to highlight individual trend shapes. | | Visual type | Line, Area line | Line | Area line adds a shaded area beneath the line. | | Line color | Color picker | Theme color | Custom color for the sparkline line. | | Line interpolation | Linear, Smooth, Stepped | Linear | Controls how points are connected. | ## Editing and removing sparklines To edit a sparkline, open the **Visuals** dropdown in the **Format visual** pane and choose the edit icon next to the sparkline you want to modify. Update the settings and choose **Apply**. To remove a sparkline, open the edit pane for the sparkline and choose **Delete**. ## Automatic removal Quick automatically removes sparklines when field changes make them invalid: + All **Group by** fields are removed – all sparklines are removed. + A sparkline's value column is removed from the **Values** field well – that sparkline is removed. + A sparkline's X-axis field is added to the **Group by** field well – that sparkline is removed. A notification appears when a sparkline is automatically removed. ## Sparkline limitations Consider the following when working with sparklines: + **Maximum sparklines per table** – Up to 3 sparkline columns per table visual + **Maximum data points** – Up to 52 data points per sparkline. If your data exceeds this limit, Quick displays the last 52 data points according to your X-axis sort order. + **Field requirements** – At least one field in the **Group by** field well and one field in the **Values** field well + **X-axis constraint** – The X-axis field cannot be the same as any **Group by** field + **Exclusive value column usage** – A value column cannot be used by both a sparkline and a data bar + **Export support** – Sparklines are included in PDF exports but not in CSV or Excel exports + **Filter behavior** – Filters applied to the table also filter sparkline data # Map and geospatial chart formatting options in Quick Map and geospatial chart options In Amazon Quick, you can choose from multiple formatting options for your maps and geospatial charts. You can view formatting options by opening the **Properties** pane from the on-visual menu located at the top right of the currently selected geospatial map. Quick authors and readers can also toggle the different formatting options of a geospatial map visual from the on visual menu. ![\[Toggle geospatial map formatting options from the on-visual menu.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/geospatial-map-options-1.gif) **Topics** + [ # Base maps on geospatial maps in Quick ](base-maps.md) + [ # Geospatial heatmaps in Amazon Quick ](heat-maps.md) + [ # Marker clustering on geospatial point maps in Quick ](marker-clustering-on-maps.md) # Base maps on geospatial maps in Quick Base maps When you create a map visual in Quick, you can change the base of the map. A *base map* is the style of map that appears beneath your data on a map. An example is a satellite view versus a street view. In Quick, there are four options for base maps: light gray canvas, dark gray canvas, streets, and imagery. The following list contains an example of each base map option: **Important** Only the light gray canvas is supported in the Asia Pacific (Mumbai) Amazon Region (ap-south-1). + Light gray canvas ![\[This is an example image of a map visual with the light gray canvas base.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/map-layers1.png) + Dark gray canvas ![\[This is an example image of a map visual with the dark gray canvas base.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/map-layers2.png) + Streets ![\[This is an example image of a map visual with the streets base.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/map-layers3.png) + Imagery ![\[This is an example image of a map visual with the imagery base.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/map-layers4.png) ## Changing base maps Use the following procedure to change a base map. **To change a base map** 1. Create a point or filled map in an analysis. For more information, see [Creating maps and geospatial charts](geospatial-charts.md). 1. On the map visual, choose the **Format visual** icon. 1. In the **Properties** pane that opens, choose the **Base map** section and then choose the base map that you want. # Geospatial heatmaps in Amazon Quick Heatmaps Use geospatial heatmaps to reveal patterns of marker concentration in your geospatial visuals. Heat maps display concentrations of data points using a colored overlay that highlights the intensity or concentration of the visual's markers. ![\[This is an example of marker clustering at work.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/heat-map-1.png) **To turn a geospatial map into a heat map** 1. Open your analysis and choose the geospatial map that you want to format. When you select a visual, it displays with a highlight around it. 1. To open the formatting pane, select the **Format visual** icon from the on-visual menu. 1. On the formatting pane at left, choose **Points**. 1. Choose **Heatmap**. 1. (Optional) For **Heatmap gradient**, choose a color that you want for the **High density** and **Low density** values. # Marker clustering on geospatial point maps in Quick Marker clustering Use marker clustering to improve readability of collocated points on a map. Geospatial locations on point maps are represented using markers. Usually, there is one marker per data point. However, if there are too many markers close together, the map becomes difficult to read. To make it easier to interpret the map, you can enable marker clustering to represent groupings of locations on the map. As the reader zooms in on the map, the clustered markers leave the area marker to display separately. ![\[This is an example of marker clustering at work.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/map-marker-clustering.gif) **To add cluster points to a map** 1. Open your analysis, and choose the geospatial map that you want to format. When you select a visual, it displays with a highlight around it. 1. To open the formatting pane, select the **Format visual** icon from the on-visual menu. 1. On the formatting pane at left, choose **Points**. 1. Choose one of the following options: + **Basic** – use the default display setting for map points. + **Cluster points** – cluster map points together when there are many in one area. # Axes and grid lines on visual types in Quick Axes and grid lines When you create a chart in Quick, axis lines, axis labels, axis sort icons, and grid lines are added to the chart automatically. You can format your visuals to show or hide these if you want, and also customize the axis label size and orientation. You can format axis lines, grid lines, and axis labels and axis sort icons for the following chart types: + Bar charts + Box plot charts + Combo charts + Histograms + Line charts + Scatter plots + Waterfall charts **To format axis lines, axis labels, and grid lines in a chart** 1. On the analysis page, choose the visual that you want to format. 1. On the menu in the upper-right corner of the visual, select the format visual icon. The **Properties** pane opens at left. **To show or hide axis lines** 1. In the **Properties** pane, choose the axis that you want to format. 1. Choose **Show axis line**. Clear the check box to hide the axis line for the chosen axis. Select the check box to show it. **To customize axis titles** 1. In the **Properties** pane, choose the axis that you want to format. 1. Choose **Show title**. Clear the check box to hide the axis title and drop-down caret icon for the chosen axis. Select the check box to show them. 1. To change the title from the default field name, enter a title in the text box. **Note** In addition to the chart types listed previously in this topic, you can also customize the axis titles in pie charts, donut charts, funnel charts, heat maps, and tree maps. **To modify axis font settings** 1. In the **Properties** pane, choose the axis that you want to format. 1. Adjust the following properties: + **Font family** + **Text size** + **Style** (Bold, Italic, Underline) + **Color** **Note** **Underline** is supported for axis titles, but not for axis labels Different chart types use different terminology: **Bar/Line charts** - **X-axis** and **Y-axis** **Pie charts** - **Values** **Heat maps** - **Rows** and **Columns** **To show or hide the sort icon** 1. In the **Properties** pane, choose the axis that you want to format. 1. Choose **Show sort**. Clear the check box to hide the sort icon for the chosen axis. Select the check box to show it. When you choose to remove the sort icon, the sort icon is removed from the axis. Any sorts that were applied to the visual before removing the icon are not removed from the visual. **Note** In addition to the chart types listed previously in this topic, you can also show or hide the sort icon in pie charts, donut charts, funnel charts, heat maps, and tree maps. **To show or hide the data zoom** 1. In the **Properties** pane, choose **X-axis**. 1. Choose **Show data zoom**. Clear the check box to hide the data zoom. Select the check box to show it. The data zoom bar appears automatically on charts with an X-axis that contain more than one data point. Adjust the bar from the left and right to zoom to specific data points in the chart. **Note** If you zoom in or out using the data zoom bar, and then choose to hide the data zoom bar, the zoom position isn't maintained. The visual zooms completely out to include all data points. Showing the data zoom again returns the visual to its previous state. **To show or hide axis labels** 1. In the **Properties** pane, choose the axis that you want to format. 1. Choose **Show labels**. Clear the check box to hide the axis labels for the chosen axis. Select the check box to show it. **To change the label size** 1. In the **Properties** pane, choose the axis that you want to format. 1. For **Label size**, choose a size. **To change the label orientation** 1. In the **Properties** pane, choose the axis that you want to format. 1. For **Label orientation**, choose an orientation. **To show or hide grid lines** 1. In the **Properties** pane, choose the axis that you want to format. 1. Choose **Show grid lines**. Clear the check box to hide grid lines for the chosen axis. Select the check box to show it. # Colors in visual types in Quick Colors You can change the color of one, some, or all elements on the following types of charts: + Bar charts + Donut charts + Gauge charts + Heat maps + Line charts + Scatter plots + Tree maps To change colors on bar charts, donut charts, gauge charts, line charts, and scatter plots, see [Changing colors on charts](#format-colors-on-charts). To change colors on heat maps and tree maps, see [Changing colors on heat maps and tree maps](#format-colors-on-heatmaps-and-treemaps). ## Changing colors on charts You can change the chart color used by all elements on the chart, and also change the color of individual elements. When you set the color for an individual element, it overrides the chart color. For example, suppose that you set the chart color to green. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/color-priority1.png) All of the bars turn green. Even though you choose the first bar, the chart color applies to all the bars. Then you set the color for the **SMB** bar to blue. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/color-priority2.png) Looking at the result, you decide that you need more contrast between the green and blue bars, so you change the chart color to orange. If you are changing the chart color, it doesn't matter which bar you choose to open the context menu from. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/color-priority3.png) The **SMB** bar remains blue. This is because it was directly configured. The remaining bars turn orange. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/color-priority4.png) When you change the color of an element that is grouped, the color for that element is changed in all of the groups. An example is a bar in a clustered bar chart. In the following example, Customer Segment is moved out of the **Y-axis** and into the **Group/Color** field well. Customer Region is added as the **Y-axis**. The chart color stays orange, and SMB stays blue for all Customer Regions. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/color-priority5.png) If your visual has a legend that shows categories (dimensions), you can click on the values in the legend to see a menu of available actions. For example, suppose that your bar chart has a field in the **Color** or **Group/Color** field well. The bar chart menu displays the actions that you can choose by clicking or right-clicking on a bar, such as the following: + Focusing on, or excluding, visual elements + Changing colors of visual elements + Drilling down into a hierarchy + Custom actions activated from the menu, including filtering or URL actions Following is an example of using the legend to change the color for a dimension. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/visual-elements-legend-color.png) ### Setting new colors for a visual Use the following procedure to change the colors for a visual. **To change the colors for a visual** 1. On the analysis page, choose the visual that you want to modify. 1. To change the chart color, choose any element on the visual, and then choose **Chart Color**. To select elements, do the following: + On a bar chart, choose any bar. + On a line chart, choose the end of a line. + On a scatter plot, choose an element. The field must be in the **Group/Color** section of **Field wells**. 1. Choose the color that you want to use. You can choose a color from the existing palette, or you can choose a custom color. To use a custom color, enter the hexadecimal code for that color. All elements on the visual are changed to use this color, except for any that have previously had their color individually set. In that case, the element color overrides the chart color. 1. To change the color for a single element on the visual, choose that element, choose **Color **, and then choose the color that you want to use. You can choose a color from the existing palette, or you can choose a custom color. To use a custom color, enter the hexadecimal code for that color. Repeat this step until you have set the color on all elements that you want to modify. To change the color back to the color it was originally, choose **Reset to default**. ### Setting visual colors back to defaults Use the following procedure to return to using the default colors on a visual. **To return to default colors on a visual** 1. On the analysis page, choose the visual that you want to modify. 1. Choose **Chart Color**, choose any element on the visual, and then choose **Reset to Default**. Doing this changes the chart color back to the default color for that visual type. All elements on the visual are changed to the default color for the visual type, except for any that have previously had their color individually set. In that case, the element color setting overrides the chart color setting. 1. To change the color for a single element back to the default, choose that element, choose **Color **, and then choose **Reset to Default**. The default color for individual elements is the chart color if you have specified one, or the default color for the visual type otherwise. ## Changing colors on heat maps and tree maps **To change the colors that display on a heat map or a tree map** 1. Choose the heat map or tree map that you want to edit. 1. Choose **Expand** for the settings menu, and choose the cog icon to open the **Properties** panel. 1. For **Color**, choose the settings that you want to use: 1. For **Gradient color** or **Discrete color**, choose the color square next to the color bar, and then choose the color that you want to use. Repeat for each color square. The bar holds two colors by default. 1. Select the **Enable 3 colors** check box if you want to add a third color. A new square appears in the middle of the color bar. You can enter a number that defines the midpoint between the two main gradient colors. If you add a value, the middle color represents the number you entered. If you leave this blank, the middle color acts like the other colors in the gradient. 1. Select the **Enable steps** check box if you want to limit the chart to the colors that you chose. Doing this changes the label on the color bar from **Gradient color** to **Discrete color**. 1. For **Color for Null Value**, choose a color to depict NULL values. This option is only available on heat maps. # Working with field level coloring in Amazon Quick Field colors With field level coloring, you can assign specific colors to specific field values across all visuals in a Quick analysis or dashboard. Colors are assigned on a per-field basis to simplify the process of setting colors and ensure consistency across all visuals that use the same field. For example, let's say you're a shipping company that wants to create a set of visuals that track shipping rates in different regions. With field level coloring, you can assign each region a different color to represent the field across all visuals in an analysis or dashboard. This way, account readers quickly learn what field colors they're looking for and have an easier time finding the information that they need. Quick authors can configure up to 50 field based colors per field. Colors that are defined at the visual level take precedence over field based colors. This means that if the author sets a color for a value on the visual, that color will override the field based colors configuration for that individual visual. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/field-coloring.gif) **To apply field level coloring to a legacy account** 1. In the **Fields** pane of the analysis, choose the ellipsis (three dots) next to the field that you want to assign a color to, and then choose **Edit field colors**. 1. In the **Edit field colors** pane that appears, choose the value that you want to assign a color to and choose the color that you want. You can apply colors to every value that appears in the **Field values** pane. 1. When you are finished assigning colors to the fields that you want, choose **Apply**. If you want to reset the color value of a field, open the **Edit field colors** pane and choose the refresh icon next to the field that you want to reset. You can reset all color values in an analysis by choosing **RESET COLORS**. You can view a list of unused colors that can be configured to new fields by choosing **Show unused colors** in the **Edit field colors** pane. When you reset a field's color, the discarded color is added to the **Unused colors** list and can be assigned to a new field. # Conditional formatting on visual types in Quick Conditional formatting In some visual types, you can add conditional formatting to highlight some of your data. The conditional formatting options currently supported include changing text or background color and using symbolic icons. You can use icons from the provided set, or you can use Unicode icons instead. Conditional formatting is available on the following visuals: + Gauge charts + Key performance indicators (KPIs) + Pivot tables + Tables For tables and pivot tables, you can set multiple conditions for fields or supported aggregations, along with format options to apply to a target cell. For KPIs and gauge charts, you can format the primary value based on conditions that are applied to any dimension in the dataset. For gauge charts, you can also format the foreground color of the arc based on conditions. **To use conditional formatting on a visual** 1. On the analysis page, choose the visual that you want to format. 1. On the visual, open the context menu on the down icon at the upper-right. Then choose **Conditional formatting**. Options for formatting display on the left. Choose one of the following: + ****For pivot tables**** – Begin by choosing a measure that you want to use. You can set conditional formatting on one or more fields. The selection is limited to the measures that are in the **Values** field well. + ****For tables**** – Begin by choosing a field that you want to use. You can set conditional formatting on one or more fields. You can also choose to apply formatting to the entire row. Formatting the entire row adds an option to **Apply on top**, which applies the row formatting in addition to formatting added by other conditions. + ****For KPIs**** – Apply formatting to the primary value or the progress bar or both. 1. For the remaining steps in this procedure, choose the features that you want to use. Not all options are available for all visuals. 1. (Optional) Choose **Add background color** to set a background color. If a background color is already added, choose **Background**. + **Fill type** – The background color can be **Solid** or **Gradient**. If you choose to use a gradient, additional color options display, enabling you to choose a minimum and maximum value for the gradient scale. The minimum value defaults to the lowest value, and the maximum value defaults to the highest value. + **Format field based on** – The field to use when applying the format. + **Aggregation** – The aggregation to use (displays only the available aggregations). + **Condition** – The comparison operator to use, for example "greater than". + **Value** – The value to use. + **Color** – The color to use. + **Additional options:** In pivot tables, you can set what you want to format by choosing options from the context menu (**…**): **Values**, **Subtotals**, and **Totals**. 1. (Optional) Choose **Add text color** to set a text color. If a text color is already added, choose **Text**. + **Format field based on** – The field or item to use when applying the format. + **Aggregation** – The aggregation to use (displays only the available aggregations). This option applies to tables and pivot tables. + **Condition** – The comparison operator to use, for example "greater than". + **Value** – The value to use. + **Color** – The color to use. + **Additional options:** In tables and pivot tables, you can set what you want to format by choosing options from the context menu (**…**): **Values**, **Subtotals**, and **Totals**. 1. (Optional) Choose **Add icons** to set an icon or icon set. If an icon is already added, choose **Icon**. + **Format field based on** – The field or item to use when applying the format. + **Aggregation** – The aggregation to use (displays only the available aggregations). This option applies to tables and pivot tables. + **Icon set** – The icon set to apply to field in **Format field based on**. This option applies to tables and pivot tables. + **Reverse colors** – Reverses the colors of the icons for tables and pivot tables. + **Custom conditions** – Provides more icon options for tables and pivot tables. + **Condition** – The comparison operator to use. + **Value** – The value to use. + **Icon** – The icon to use. To choose an icon set, use the **Icon** symbol to choose the icons to use. Choose from the provided icon sets. In some cases, you can add your own. To use your own icon, choose **Use custom Unicode icon**. Paste in the Unicode glyph that you want to use as an icon. Choose **Apply** to save or choose **Cancel** to exit icon setup. + **Color** – The color to use. + **Show icon only** – Replaces the value with the icon for tables and pivot tables. + **Additional options:** + In tables and pivot tables, you can set what you want to format by choosing options from the context menu (**…**): **Values**, **Subtotals**, and **Totals**. + In pivot tables, enabling **Custom conditions** activates preset conditional formatting that you can keep, add to, or overwrite with your own settings. 1. (Optional) Choose **Add foreground color** to set the foreground color of a KPI progress bar. If a foreground color is already added, choose **Foreground**. + **Format field based on** – The field to use when applying the format. + **Condition** – The comparison operator to use. + **Value** – The value to use. + **Color** – The color to use. 1. When you are finished configuring conditional formatting, choose one or more of the following: + To save your work, choose **Apply**. + To cancel selections and return to the previous panel, choose **Cancel**. + To close the settings panel, choose **Close**. + To reset all settings on this panel, choose **Clear**. # KPI options You can customize KPIs in Amazon Quick to meet your business needs. You can add contextual sparklines or progress bars, assign primary and secondary values, and add conditional formatting to your KPIs. To format a KPI in Quick, navigate to the KPI that you want to change and choose the **Format visual** icon to open the **Format visual**. Use the following procedures to perform formatting tasks for KPIs. ## Add a visual to a KPI You can choose to add an area sparkline, a sparkline, or a progress bar to any KPI in Quick. Adding visuals to KPIs provides visual context to readers who are viewing KPI data. Use the following procedure to add a visual to a KPI. **To add a visual to a KPI** 1. Navigate to the KPI that you want to change and open the format visual menu. 1. In the **Properties** menu, choose the **Visual** box to display a visual on your KPI chart. 1. (Optional) Open the **Visual** dropdown and choose the type of visual that you want to display on your KPI. You can choose to display an area sparkline, a sparkline, or a progress bar. To display a sparkline, make sure that your KPI has a value in the **Trend** field well. **Area sparkline** is the default value. 1. (Optional) To change the color of the sparkline, choose the color icon to the left of the **Visual** dropdown and choose the color that you want. Color formatting isn't supported for the progress bar. 1. (Optional) Choose **Add tooltip** to add a tooltip to the KPI visual. ## Customizing primary and secondary values Customize values Use the **Format visual** menu to customize the font, color, and to choose which primary value is displayed. You can also choose to display a secondary value. **To customize the primary and secondary values of a KPI** 1. Navigate to the KPI that you want to change, open the **Format visual** menu, and navigate to the **KPI** section. 1. For **Primary value**, use the **Font** dropdown to choose the font size that you want. The default value is **Auto**. 1. (Optional) To change the color of the primary value's font, choose the color icon next to the **Font** dropdown, and then choose the color that you want. 1. For **Primary value displayed**, you can choose to display the actual value or the comparison value of the primary value. 1. To add a secondary value, choose **Secondary value**. 1. (Optional) Use the **Font** dropdown to choose the font size that you want. The default value is **Extra large**. 1. (Optional) To change the color of the secondary value's font, choose the color icon next to the **Font** dropdown, and then choose the color that you want. ## Conditional formatting options for KPIs Conditional formatting Conditional formatting for KPIs is automatically set for comparison values. By default, positive values are represented in green and negative values are represented in red. You can customize the color values of these color values from the **Properties** pane. **To change the color of positive and negative values** 1. In the **Properties** pane, open the **Conditional formatting** section and choose the comparison value that you want to change. 1. To change the color of the positive value, navigate to **Condition \$11**, choose the **Color** icon, and then choose the color tht you want. 1. To change the color of the negative value, navigate to **Condition \$12**, choose the **Color** icon, and then choose the color tht you want. 1. When you are finished making the changes that you want, choose **Apply**. You can also add text colors and icons for the **Actual value** in thee **Conditional formatting** menu. To add a text color or icon to the actual value, choose **Add text color** or **Add icon** to set the new values. # Labels on visual types in Quick Labels Use the following procedure to customize, display, or hide the labels for a visual. **To customize, display, or hide the labels for a visual** 1. On the analysis page, choose the visual that you want to format. You can change the labels by choosing the label directly on the visual, and choosing **Rename**. To revert to the default name, delete your entry. 1. To see more options, choose the on-visual menu from the down icon at the upper-right corner of the visual, and then choose the **Format visual** icon. For pivot tables, you can relabel row names, column names, and value names. Additionally, under **Styling**, you can choose to hide columns labels or metric labels (for single metrics only). You can add the same value to the same visual multiple times. You can do so to show the same value with different aggregations or table calculations applied. By default, the fields all display the same label. You can edit the names by using the **Properties** panel, which you open by choosing the **V**-shaped icon at top right. 1. On the **Properties** pane, enable or disable **Show title**. This option removes the axis title. 1. Close the **Properties** pane by choosing the **X** icon in the upper-right corner of the pane. # Data labels on visual types in Quick Data labels To customize data labels on a visual, you can use the **Properties** pane to show data labels, and then use the settings to configure them. Data label customization is supported on bar, line, combo, area, scatterplot, donut, boxplot, waterfall, heatmap, treemap, histogram, funnel, sankey, gauge, radar, and pie charts. You can customize the following options: + Position, which determines where the label appears in relation to the data point (for bar, combo, and line charts): + For vertical bar charts, you can customize to set position: + Above bars + Inside of bars + Bottom of bars + Top of bars + For horizontal bar charts, you can customize to set position: + Right of bars + Inside of bars + For line charts, you can customize to set position: + Above lines + Left or right of points on lines + Below lines + For scatter charts, you can customize to set position: + Above points + Left or right of points + Below points + Font size and color (for bar, combo, line, scatter, and pie charts) + Label pattern, which determines how data is labeled (for bar, combo, line, and scatter charts): + For bar, combo, and scatter charts, you can label: + All + By group or color + For line charts, the following label options are available: + All + By group or color + Line ends + Minimum or maximum value only + Minimum and maximum values + For pie charts, the following label options are available: + Show category + Show metric + Choose to show the metric label as value, percent, or both + Group selection (for bars and lines, when the label pattern is "by group/color") + Allow labels to overlap (for bars and lines), for use with fewer data points + For vertical bar, combo, and line charts, labels that are too long are angled by default. You can configure the degree of angle under the **X-axis** settings. **Note** If you add more than one measure to an axis, the data label displays the formatting for the first measure only. **To configure data labels** 1. On the analysis page, choose the visual that you want to format. 1. Choose the on-visual menu from the down icon at the upper-right corner of the visual, and then choose the **Format visual** icon. 1. On the **Properties** pane, choose **Data Labels**. 1. Enable **Show data labels** to show and customize labels. Disable this option to hide data labels. 1. Choose the settings that you want to use. The settings offered are slightly different for each chart type. To see all available options, see the list before this procedure. You can immediately view the effect of each change on the visual. 1. To modify the data label font settings, adjust the following properties: + **Font family** + **Text size** + **Style** (Bold, Italic) + **Color** 1. Close the **Properties** pane by choosing the X icon in the upper-right corner of the pane. # Formatting visual numeric data based on language settings in Quick Language formatting for numeric data In Amazon Quick, you can choose how your numeric data values appear in visuals so that they align with the regional language that you have chosen. As a Quick author, you can choose the language formatting that best fits your audience. Amazon Quick configures numeric data languages at the analysis level based on the language that you have chosen to view Quick in. You can change the format of numbers, currencies, and dates. You can change your Quick language settings in the **Language** dropdown list of the Quick **User** menu in the top-right corner. You can change the language formatting for a field across every visual in a sheet, or you can change the language formatting at the individual visual level. **To change the numeric language formatting of all visuals in an analysis** 1. On the **Visuals** pane of the analysis that you want to change, choose the more actions (three dots) icon next to the field that you want to change. From the menu that appears, open the **Format** dropdown list, and then choose **More formatting options**. 1. In the **Format data** pane that appears on the left, choose **Apply language format**. You can reset the default language format of the field by reopening the **Format data** menu and choosing **Reset to defaults**. The default language format is American English. **To change the numeric language formatting of a single visual in an analysis** 1. On the analysis page, choose the visual that you want to modify. 1. Navigate to the **Format data** pane using one of the following options: + On the visual that contains the data that you want to change, select the field that you want to change, open the **Format** dropdown list, and then choose **More formatting options**. ![\[Access the Format data pane in the visual.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/format-visual-numeric-data-language-3.png) + In the **Field wells** section of the analysis, open the dropdown next to the field that you want to change. Open the **Format** menu, and choose **More formatting options**. ![\[Access the Format data pane from the field wells.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/format-visual-numeric-data-language-6.png) 1. In the **Format data** pane that appears, choose **Apply language format**. You can reset the default language format of the visual by reopening the **Format data** menu and choosing **Reset to defaults**. The default language format is American English. # Legends on visual types in Quick Legends The *visual legend *helps you identify what a visual element represents by mapping its value to a color. By default, the visual legend displays to the right of the visual. You can choose to hide or display the visual legend, and format the legend title and position. You can also customize the font settings for the legend title and items. **To display or hide a visual legend** 1. Sign in to Quick at [https://quicksight.aws.amazon.com/](https://quicksight.aws.amazon.com/). 1. On the analysis page, choose the visual that you want to format. 1. Choose the visual that you want to format, and then choose the **Properties** icon to open the Properties pane. 1. Toggle the **Legend** on to display the visual's legend. When shown, the legend displays the values in alphabetical order. To hide the legend, toggle the **Legend** switch off. **To customize a visual legend** 1. Open the Properties pane and expand the **Legend** section. 1. Use the **Position** dropdown to customize the position of the legend in the visual. 1. For **Legend title**, enter a custom name for the legend and perform all or some of the following actions: 1. (Optional) To change the color of the legend title, choose the color swatch underneath the legend title, and then choose the color that you want the legend title to be. 1. (Optional) To change the font or font size of the legend title, open the **Font** or **Font size** dropdown and choose the font or font size that you want. 1. (Optional) To bold, italicize, or underline the legend title, choose the appropriate icon from the style bar. 1. For **Legend item**, perform all or some of the following actions: 1. (Optional) To change the color of the legend item font, choose the color swatch, and then choose the color that you want the legend title to be. 1. (Optional) To change the font or font size of the legend item, open the **Font** or **Font size** dropdown and choose the font or font size that you want. 1. (Optional) To bold, italicize, or underline the legend item font, choose the appropriate icon from the style bar. 1. Choose the **X** icon at upper right to close the **Properties** pane. # Line and marker styling on line charts in Quick Lines and markers in line charts In Quick line charts, you have multiple options to emphasize what you want readers to focus on: color, line style, and markers. You can use these options together or separately to help readers understand your line charts more quickly under different circumstances. For example, if some of your readers won't see color differences—perhaps because of color blindness or because of monochrome printing—you can use line patterns to distinguish one ore more lines in a chart. In other cases, you could use step lines to call attention to abrupt changes or intervals between changes in data. For example, let's say you build a chart showing the changing price of postage stamps in the US, and you want to emphasize the amount of increase in price over time. You can use a step line, which remains flat between data points until the next price change occurs. The data story about abrupt increases in price is more clear to the reader with a step line. If you wanted to show a story of gradual change over time, you'd be more likely to style the line with a smooth slope instead. **To customize the styling for a visualization** 1. Open your analysis, and choose the chart that you want to format. 1. On the top right of the visual you want to format, select **Format visual**, which is represented by a pencil icon. 1. At left, choose **Data series**. 1. Choose one of the following options: + **Base style** – to edit the styling of all lines and markers on the chart + **Select series to style** – to edit the styling of the field that you choose from the list Different options display depending on how many compatible fields are in the visual. 1. Toggle **Line** to turn line styling on or off. You can customize the following line options: + The weight or thickness of the line. + The style of the line: solid, dashed, or dotted. + The color of the line. + The type of line that it is: Linear, Smooth, or Stepped. 1. Toggle **Marker** to turn marker styling on or off. You can customize the following marker options: + The weight or thickness of the marker. + The style of the marker: circle, triangle, square, diamond, and so on. + The color of the marker. 1. For **Axis**, choose whether to display the axis on the left or the right. 1. Your changes are saved automatically. 1. (Optional) To undo customizations, choose one or more of the following options: + To undo one change, click the undo arrow at top left. Repeat as needed. There is also a redo arrow. + To reset the base style for a data series, select **Base style **and then click **Reset to default**. + To remove all styling from a data series, listed in **Styled series**, select a field and then click **Remove styling**. # Missing data on visual types in Quick Missing data You can customize how missing data points are visualized in your line charts and area charts. You can choose to have your missing data points appear in the following formats: + *Broken line*: A disjointed line that breaks when a data point is missing. This is the default missing data format. + *Continuous line*: Displays a continuous line by skipping over the missing data point and connecting the line to the next available data point in the series. To show a continuous line, the **Show date gaps** box on the **X axis** pane should be unchecked. + *Show as zero*: Sets the value of the missing data point to zero. **To customize a visual's missing data settings** 1. On the analysis page, choose the visual that you want to format. 1. Choose the **Format visual** icon in the upper right corner of the visual to access the **Format visual** menu. 1. Open the **Y axis** pane of the format visual menu and navigate to the **Missing data** section. 1. Select the missing data format that you want. # Reference lines on visuals types in Quick Reference lines *Reference lines* are visual markings in a visual, similar to ruler lines. You typically use a reference line for a value that needs to be displayed with the data. You use the reference line to communicate thresholds or limits in values. The reference line isn't part of the data that's used to build a chart. Instead, it's based on a value that you enter or a field that you identify in the dataset used by a chart. ![\[alt text not found\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/formatting-reference-lines-example.png) Quick supports reference lines in the following: + Bar charts + Line charts + Combo charts You can create, change, and delete reference lines while designing an analysis. You can customize the line pattern, the label font, and the colors for each of those separately. You can show numeric values as numbers, currency, or percent. You can also customize a value's numerical format in the same way that you can customize a field in the field well. There are two types of reference lines: + A *constant line* displays at a position that's based on a value that you specify in the format settings. This value doesn't need to relate to any field. You can customize the formatting of the line. + A *calculated line* displays at a position that's based on a value that is the result of a function. During configuration, you specify which measure (metric) you want to use and which aggregation to apply. These are the same aggregations you can apply to in the field wells. Then, you need to provide an aggregation to apply to the field calculation for the reference line, for example average, minimum, maximum, or percentile. The field needs to be in the dataset used by the chart, although it doesn't need to be displayed in the chart's field wells. Calculated reference lines aren't supported in 100% stacked charts. **To add or edit a reference line (console)** 1. Open the [Quick console](https://quicksight.aws.amazon.com/). 1. Open the analysis that you want to change. 1. Choose the visual that you want to change and open the **Properties** menu. 1. In the **Properties** pane that opens, open the **Reference lines** dropdown, and then choose **ADD NEW LINE**. 1. The **New reference line** menu opens. Use this menu to configure your new reference line. The list below describes all reference line properties that can be configured. + **Data** + **Type** – The type of reference line that you want to use. Choose one of the following options: + To create a constant line based on a single value that you enter, choose **Constant line**. + To create a calculated line based on a field, choose **Calculated line**. + **Value** – (For constant lines only) The value that you want to use. This becomes the location of the line on the visual. It appears immediately, so you can experiment with the setting. + **Column** – (For calculated lines only) The column that you want to use for the reference line. + **Aggregated as** (column) – (For calculated lines only) The aggregation that you want to apply to the selected column. + **Calculate** – (For calculated lines only) The calculation that you want to apply to the aggregation. + **Percentile value** – (Only if you set **Calculate** to **Percentile**) Enter a number from 1 through 100. + **Chart type** – (For combo charts) Choose **Bars** or **Lines**. + **Line style** + **Pattern** – The pattern used for the line. Valid options include **Dashed**, **Dotted**, and **Solid**. + **Color** – The color used for the line. + **Label** + **Type** – The type of label to display. Valid options include **Value only**, **Custom text**, **Custom text and value**, **No label**. If you choose an option that includes custom text, enter the label text that you want to appear on the line. + **Enter custom text** (text box) – (Only if you set **Type** to **Custom text and value**) Choose where to show the value in relation to the label. Valid options are **Left** or **Right**. + **Position** – The position of the label in relation to the line. Valid options include a combination of the following: left, middle, right, above, and below. + **Value format** – The format to use for the value. Choose one of the following: + **Same as value** – Uses the formatting that's already selected for this field in the visualization. + **Show as** – Choose from the available options, for example number, currency, or percent. + **Format**– Choose from the available formatting options. + **Font size** – The font size to use for the label text. + **Color** – The color to use for the label text. 1. Choose **Done** to save your selections. **To list existing reference lines** 1. Choose the visual that you want to change and open the **Properties** pane. 1. In the **Properties** pane, open the **Reference lines** dropdown, and then choose the ellipsis (three dots) next to the line that you want to change. 1. Choose **Edit**. 1. The **New reference line** menu opens. Use this menu to make changes to your reference line. When you are finished, choose **Done**. **To disable a reference line** 1. Choose the visual that you want to change and open the **Properties** pane. 1. In the **Properties** pane, open the **Reference lines** dropdown, and then choose the ellipsis (three dots) next to the line that you want to change. 1. Choose **Disable**. **To delete a reference line** 1. Choose the visual that you want to change and open the **Properties** pane. 1. In the **Properties** pane, open the **Reference lines** dropdown, and then choose the ellipsis (three dots) next to the line that you want to change. 1. Choose **Delete**. # Formatting radar charts in Quick Radar chart options You can customize radar charts in Amazon Quick to arrange your data the way that you want. You can customize the series style, start angle, fill area, and grid shape of a radar chart. **To set the series style of a radar chart** 1. Choose the radar chart visual that you want to change, and choose the **Format visual** icon on the top right corner of the visual. 1. In the **Properties** pane on the left, open the **Radar chart** dropdown list. 1. Under **Series style**, choose the style that you want. You can choose between the following styles: + **LINE**. When selected, the polygons that are created by the data are outlined. + **AREA**.When selected, the polygons that are created by the data are filled in. The default selected value is **LINE**. **To choose the start angle of a radar chart** 1. Choose the radar chart visual that you want to change, and choose the **Format visual** icon on the top right corner of the visual. 1. In the **Properties** pane on the left, open the **Radar chart** dropdown list. 1. Under **Start angle**, enter the start angle value that you want. The default value is 90 degrees. **To set the fill area of a radar chart** 1. Choose the radar chart visual that you want to change, and choose the **Format visual** icon on the top right corner of the visual. 1. In the **Properties** pane on the left, open the **Axis** dropdown list. 1. Select the **Fill grid lines** check box. 1. (Optional) Select colors for the even and odd numbered grid lines. + Choose the **Even color** icon that appears, and then choose the color that you want the even numbered grid lines to be. The default color for this value is white. + Choose the **Odd color** icon that appears, and then choose the color that you want the odd numbered grid lines to be. The default color for this value is white. **To choose the grid shape of a radar chart** 1. Choose the radar chart visual that you want to change, and choose the **Format visual** icon on the top right corner of the visual. 1. In the **Properties** pane on the left, open the **Radar chart** dropdown list. 1. Under **Grid shape**, choose the shape that you want the radar chart grid to be. You can choose between a **POLYGON** and a **CIRCLE**. # Range and scale on visual types in Quick Range and scale To change the scale of the values shown on the visual, you can use the **Properties** pane to set the range for one or both axes of the visual. This option is available for the value axes on bar charts, combo charts, line charts, and scatter plots. By default, the axis range starts at 0 and ends with the highest value for the measure being displayed. For the group-by axis, you can use the data zoom tool on the visual to dynamically adjust the scale. **To set the axis range for a visual** 1. On the analysis page, choose the visual that you want to format. 1. Choose the control menu at the upper-right corner of the visual, and then choose the cog icon. 1. On the **Properties** pane, choose **X-Axis** or **Y-Axis**, depending on what type of visual you are customizing. This is the **X-Axis** section for horizontal bar charts, the **Y-Axis** section for vertical bar charts and line charts, and both axes are available for scatter plots. On combo charts, use **Bars** and **Lines** instead. 1. Enter a new name in the box to rename the axis. To revert to the default name, delete your entry. 1. Set the range for the axis by choosing one of the following options: + Choose **Auto (starting at 0)** to have the range start at 0 and end around the highest value for the measure being displayed. + Choose **Auto (based on data range)** to have the range start at the lowest value for the measure being displayed and end around the highest value for the measure being displayed. + Choose **Custom** to have the range start and end at values that you specify. If you choose **Custom**, enter the start and end values in the fields in that section. Typically, you use integers for the range values. For stacked 100 percent bar charts, use a decimal value to indicate the percentage that you want. For example, if you want the range to be 0–30 percent instead of 0–100 percent, enter 0 for the start value and .3 for the end value. 1. For **Scale**, the default is linear scale. To show logarithmic scale, also called log scale, enable the logarithmic option. Quick chooses the axis labels to display based on the range of values in that axis. + On a linear scale, the axis labels are evenly spaced to show the arithmetical difference between them. The labels display the numbers in sets like \$11000, 2000, 3000…\$1 or \$10, 50 million, 100 million…\$1, but not \$110 thousand, 1 million, 1 billion…\$1. Use a *linear scale* for the following cases: + All the numbers that display on the chart are in the same order of magnitude. + You want the axis labels to be evenly spaced. + The axis values have a similar number of digits, for example 100, 200, 300, and so on. + The rate of change between numbers is relatively slow and steady—in other words, your trend line never approaches becoming vertical. Examples: + Profits in different regions of the same country + Costs incurred for manufacture of an item + On a *logarithmic scale*, the axis values are spaced to show the orders of magnitude as a way of comparing them. The log scale is often used to display very large ranges of values or percentages, or to show exponential growth. Use logarithmic scale for the following cases: + The numbers that display on the chart aren’t in the same order of magnitude. + You want the axis labels to be flexibly spaced to reflect the wide range of values in that axis. This might mean that the axis values have a different number of digits, for example 10, 100, 1000, and so on. It might also mean that the axis labels are unevenly spaced. + The rate of change between numbers is growing exponentially or is too large to display in a meaningful way. + The customer of your chart understands how to interpret data on a log scale. + The chart displays values that growing faster and faster. Moving given distance on the scale means the number has been multiplied by another number. Examples: + High yield stock prices over a long range of time + Growth of pandemic infection rates 1. To customize the number of values to show on the axis labels, enter in an integer between 1 and 50. 1. For combo charts, choose **Single Y Axis** to synchronize the Y-axes for both bars and lines into a single axis. 1. Close the **Properties** pane by choosing the **X** icon in the upper-right corner of the pane. # Small multiples axis options You can configure the x and y axes for each individual panel of a small multiples visual. You can group your data along an independent x-axis or an independent y-axis. You can also position the x and y axes inside or outside the chart to improve the readabiilty of your data. For small multiples visuals that use an independent x-axis, only the values that are relevant to each panel are shown on the axis. For example, say you have a small multiples visual that uses one panel to represent each region of the United States. With an independent x-axis, each panel only shows states in the region that the panel represents and hides states that are outside of the panel's region. For small multiples visuals that use an independent y-axis, each panel uses its own y-axis scale that is determined by the rage of the data it contains. By default, data labels appear on the inside of the panel. **To configure independent axes for small multiples visuals** 1. Select the small multiples visual that you want to change and open the **Format visual** menu. 1. In the **Properties** pane that appears, open the **Multiples options** menu. 1. For **X-axis**, choose **Independent** from the dropdown. Or, for **Y-axis**, choose **Independent** from the dropdown. You can revert your changes by choosing **Shared** from the **X-axis** or **Y-axis** dropdown menus. You can also configure the label positions of the x and y axes of all panels in a small multiples visual. You can choose to display axis labels inside or outside the panel. **To configure the axis label position for small multiples visuals** 1. Select the small multiples visual that you want to change and open the **Format visual** menu. 1. In the **Properties** pane that appears, open the **Multiples options** menu. 1. For **X-axis labels**, choose **Inside** or **Outside** from the dropdown. Or, for **Y-axis labels**, choose **Inside** or **Outside** from the dropdown. # Titles and subtitles on visual types in Quick Titles and subtitles In Quick, you can format visual titles and subtitles to meet your business needs. Quick offers rich text formatting for titles and subtitles, and the ability to add hyperlinks and parameters in titles. You can edit titles in the Properties pane, or by double-clicking on a title or subtitle in the visual. Use the following procedure to customize the way the title and subtitle of a visual is displayed. The visual title is shown by default. After subtitles are created, they're also shown by default. 1. Sign in to Quick at [https://quicksight.aws.amazon.com/](https://quicksight.aws.amazon.com/). 1. Open the analysis that you want to update. 1. On the analysis page, choose the visual that you want to format. 1. At the visual's right, choose the **Properties** icon. 1. In the **Properties** pane that opens, choose the **Display settings** tab. 1. To edit the title or subtitle of a visual, choose the paintbrush icon next to **Edit title** or **Edit subtitle**. Alternatively, you can choose the eyeball icon next to **Edit title** or **Edit subtitle** to hide the title or subtitle, shown in the following image. 1. In the **Edit title** or **Edit subtitle** popup that opens, you can use the following options to make the updates that you want: + To enter a custom title or subtitle, enter your title or subtitle text in the editor. Titles can be up to 120 characters long, including spaces. Subtitles can be up to 500 characters long. + To change the font type, choose a font type from the list at left. + To change the font size, choose a size from the list at right. + To change the font weight and emphasis, or to underline or strikethrough text, choose the bold, emphasis, underline, or strikethrough icons. + To change the font color, choose the color (Abc) icon, and then pick a color. You can also enter a hexadecimal number or RGB values. + To add an unordered list, choose the unordered list icon. + To change the text alignment, choose the left, center, or right alignment icons. + To add a parameter to a title or subtitle, choose an existing parameter from the list under **Parameters** at right. For more information about how to create parameters, see [Setting up parameters in Amazon Quick](parameters-set-up.md). + To add a hyperlink, highlight the text that you want to link, choose the hyperlink icon, and then choose from the following options: + For **Enter link**, enter the URL that you want to link to. Choose the \$1 icon at right to add an existing parameter, function, or computation to the URL. + To edit the display text, enter text for **Display text**. + To open the hyperlink in the same browser tab as Quick, select **Same tab**. + To open the hyperlink in a new browser tab, select **New tab**. + To delete the hyperlink, choose the delete icon at bottom left. When finished configuring the hyperlink, choose **Save**. 1. When you are finished, choose **Save**. 1. For **Alt text**, enter the alt text that you want for the visual. 1. When you are finished, close the properties pane. # Tooltips on visual types in Quick Tooltips When you hover your cursor over any graphical element in an Quick visual, a tooltip appears with information about that specific element. For example, when you hover your cursor over dates in a line chart, a tooltip appears with information about those dates. By default, the fields in the Fields well determine what information displays in tooltips. Tooltips can display up to 10 fields. You can provide your viewers with additional information about data in your visual, customizing what viewers can see. You can even prevent tooltips from appearing when viewers hover a cursor over an element. To do this, you can customize the tooltips for that visual. ## Customizing tooltips in a visual Use the following procedure to customize tooltips in a visual. **To customize tooltips in a visual** 1. On the analysis page, choose the visual that you want to format. 1. On the menu in the upper-right corner of the visual, choose the **Format visual** icon. 1. In the **Properties** pane that opens, choose **Tooltip**. 1. For **Type**, choose **Detailed tooltip**. A new set of options appear. **To show or hide titles in a tooltip** + Choose **Use primary value as title**. Clearing the option hides titles in the tooltip. Selecting the option shows the primary field value as the title in the tooltip. **To show or hide aggregations for fields in the tooltip** + Choose **Show aggregations**. Clearing the option hides the aggregation for fields in the tooltip. Selecting the option shows the aggregation for fields in the tooltip. **To add a field to the tooltip** 1. Choose **Add field**. 1. In the **Add field to tooltip** page that opens, choose **Select field** and then select a field from the list. You can add up to 10 fields to tooltips. 1. (Optional) For **Label**, enter a label for the field. This option creates a custom label for the field in the tooltip. 1. (Optional) Depending on whether you add a dimension or a measure, choose how you want the aggregation to display in the tooltip. If you don't select an option, Quick uses the default aggregation. If you add a measure to the tooltip, you can select how you want the field to be aggregated. To do so, choose **Select aggregation**, and then select an aggregation from the list. For more information about the types of aggregations in Quick, see [Changing field aggregation](changing-field-aggregation.md). 1. Choose **Save**. A new field is added to the list of fields in your tooltip. **To remove a field from the tooltip** + Under the **Fields** list, select the field menu for the field that you want to remove (the three dots) and choose **Hide**. **To rearrange the order of the fields in the tooltip** + Under the **Fields** list, select the field menu for a field (the three dots) and choose either **Move up** or **Move down**. **To customize the label for a field in the tooltip** 1. Select the field menu for the field that you want to customize (the three dots) and choose **Edit**. 1. In the **Edit tooltip field** page that opens, for **Label**, enter the label that you want to appear in the tooltip. 1. Choose **Save**. ## Using sheet tooltips in Quick Sheet tooltips transform how viewers explore data by providing rich context without disrupting their analysis flow. Instead of navigating away from a visual or opening separate sheets, viewers get instant access to detailed breakdowns, trends, and supporting information, making dashboards more intuitive and reducing the need for multiple sheets. Sheet tooltips are available on interactive sheets only. They are not supported on paginated reports. You can duplicate a tooltip sheet to another tooltip sheet, or duplicate a tooltip sheet to a regular interactive sheet. Additionally, you can duplicate a visual to a tooltip sheet. ### How sheet tooltips work When an author creates a sheet tooltip, a tooltip sheet is created and associated with a visual. This tooltip sheet works like a regular sheet. You can add visuals, text boxes, and images to it using a free-form layout. When a viewer hovers over a data point, the tooltip sheet inherits all filters from the source visual and adds an additional filter for the specific data point. For example, if your source visual is filtered to "2025 data" and a viewer hovers over "Electronics," the tooltip shows Electronics data for 2025 only. Consider a bar chart showing sales by product category. You could create a sheet tooltip that shows a trend line of monthly sales, a KPI of year-over-year growth, and a text box with the category name, all filtered to whichever category the viewer hovers over. ![\[Animated image showing a sheet tooltip appearing when hovering over data points in a visual.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/sheet-tooltip-preview.gif) ### Sheet tooltip limits The following limits apply to sheet tooltips: + Up to 50 tooltip sheets per analysis + Up to 5 visuals per tooltip sheet + Up to 5 text boxes per tooltip sheet + Up to 5 images per tooltip sheet + Tooltip sheets use free-form layout only + Layer map visuals are not allowed on tooltip sheets + Maximum size of a tooltip sheet is 640px wide by 720px tall ### Creating a sheet tooltip Use the following procedure to create a sheet tooltip for a visual. **To create a tooltip sheet** 1. On the analysis page, choose the visual that you want to add a sheet tooltip to. 1. On the menu in the upper-right corner of the visual, choose the **Format visual** icon. 1. In the **Properties** pane that opens, choose **Interactions** > **Tooltip**. 1. For **Type**, choose **Sheet tooltip**. ![\[The Properties pane showing the Sheet tooltip option selected in the Type dropdown.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/sheet-tooltip-properties-pane.png) 1. Choose **Create tooltip sheet**. You will automatically navigate to a tooltip sheet editing experience. A tooltip name is auto-generated and you can edit it by choosing the tab title. 1. Add visuals, text boxes, or images to the tooltip sheet. Arrange them using the free-form layout. 1. When you are finished, return to the source sheet by choosing the **Back** button located to the left of the sheet tooltip title. To preview the tooltip, hover over any data points in the visual. ### Assigning a tooltip sheet to a visual When you select **Sheet tooltip** as the tooltip type in the **Properties** pane, a control appears that lets you select all tooltip sheets available in the analysis. You can assign one tooltip sheet to multiple visuals or create separate tooltip sheets for each visual. If you would like to apply the same tooltip sheet to another visual, you can do this by assigning one tooltip sheet to multiple visuals in the **Interactions** > **Tooltip** accordion in the **Properties** pane. ### Editing a tooltip sheet Use the following procedure to edit an existing sheet tooltip. **To edit a tooltip sheet** 1. Choose any visual where a sheet tooltip is enabled. 1. Open the **Properties** pane and navigate to **Interactions** > **Tooltip**. 1. In the **Tooltip** accordion, select the tooltip that you would like to edit and choose the edit icon next to the tooltip sheet name to navigate to it. 1. Make your changes to the visuals, text boxes, or images on the tooltip sheet. ![\[Animated image showing how to edit a tooltip sheet.\]](http://docs.amazonaws.cn/en_us/quick/latest/userguide/images/sheet-tooltip-editing.gif) ### Switching between tooltip types You can switch a visual's tooltip between basic, detailed, and sheet tooltip types at any time. **To change the tooltip type** 1. Choose the visual that you want to update. 1. Open the **Properties** pane, choose **Interactions**, and then choose **Tooltip**. 1. For **Type**, select the tooltip type that you want: **Basic tooltip**, **Detailed tooltip**, or **Sheet tooltip**. **Note** Switching away from a sheet tooltip preserves your work. You can always switch back without losing your tooltip sheet design. ### Sheet tooltip considerations Keep the following in mind when working with sheet tooltips: + Tables and pivot tables support sheet tooltips but not basic or detailed tooltips. + Visuals in a tooltip sheet do not support context menus, on-visual menus, or custom actions. + [Using custom actions for filtering and navigating](quicksight-actions.md) on visuals in a tooltip sheet are not supported when the sheet is rendered as a tooltip. + Sheet tooltips support filters, cross-sheet filtering, and parameters. Filter controls are not supported. + Sheet descriptions are not displayed on tooltip sheets. + Cross-sheet filters cannot be scoped to tooltip sheets. + An analysis must contain at least one regular interactive sheet. An analysis cannot consist of only tooltip sheets. + Layer map visuals cannot be placed inside a tooltip sheet. + Tooltips on tooltip sheets are not supported. + Sheet tooltips are not supported on the following chart types: Sankey, Waterfall, KPI, Radar, Wordcloud, Custom content, and Highcharts. These limits ensure tooltip sheets load quickly and maintain a focused, scannable experience for viewers. For more complex analysis, consider using drill-down actions or separate detail sheets. ## Hiding tooltips in a visual If you don't want tooltips to appear when you hover your cursor over data in a visual, you can hide them. **To hide tooltips in a visual** 1. On the analysis page, choose the visual that you want to format. 1. On the menu in the upper-right corner of the visual, choose the **Format visual** icon. 1. In the **Properties** pane that opens, choose **Tooltip**. 1. Choose **Show tooltip**. Clearing the option hides tooltips for the visual. Selecting the option shows them. # Customizing data presentation To gain further insight into your data when creating visuals (charts) in an Quick analysis, you can sort and filter data in a visual. You can also change the granularity of date fields, data type, role, and format of fields in a visual. **Topics** + [ # Changing fields used by a visual in Amazon Quick ](changing-visual-fields.md) + [ # Sorting visual data in Amazon Quick ](sorting-visual-data.md) # Changing fields used by a visual in Amazon Quick Changing fields used by a visual You can add or modify fields for a visual by using the **Fields list** pane, the field wells, or the on-visual editors or drop targets on the visual. The field wells, on-visual editors, and drop targets available for a specific visual depends on the visual type selected. For details, see the appropriate visual type topic in the [Visual types in Amazon Quick Sight](working-with-visual-types.md) section. **Important** You can also change the data type and format of numeric fields by using field wells and on-visual editors. If you change a field in this way, it changes for the selected visual only. For more information about changing numeric field data types and formats, see [Changing fields used by a visual in Amazon Quick](#changing-visual-fields). Use the following topics to learn more about adding, removing, and modifying fields on a visual. **Topics** + [ # Using visual field controls ](using-visual-field-controls.md) + [ # Adding or removing a field ](adding-or-removing-a-field.md) + [ # Changing the field associated with a visual element ](changing-a-field-association.md) + [ # Changing field aggregation ](changing-field-aggregation.md) + [ # Changing date field granularity ](changing-date-field-granularity.md) + [ # Customizing a field format ](customizing-field-format.md) # Using visual field controls You can edit the fields used by a visual with user interface (UI) controls. You can use these controls as follows: + Create a visual and assign fields to different elements on it by selecting fields in the **Fields list** pane, or dragging fields to field wells or drop targets. + Change the field associated with a visual element by dragging a field to a drop target or field well, or selecting a different field in a field well or on-visual editor. + Change field aggregation or date granularity by using the field wells or the on-visual editors. The field wells, on-visual editors, and drop targets available on a specific visual depends on the visual type selected. ## Dragging fields to drop targets or field wells When you drag a field to either a drop target or field well, Amazon Quick provides you with information about whether the target element expects a measure or a dimension. Amazon Quick also provides you with information about whether that element is available for field assignment. For example, when you drag a measure to the value drop target on a new single-measure line chart, you see the drop target color-coded green. That green color coding indicates that the drop target expects a measure. The drag label indicates that the target is available to add a field. When you drag a dimension to the x-axis or color drop target on a new line chart, you see a label color-coded blue. That blue color coding indicates that the drop target expects a dimension. The drag label indicates that the target is available to add a field. You can also drag a measure or dimension to a drop target on a line chart where the element is already associated with a field. In this case, the drag label indicates that you are replacing the field currently associated with the drop target. # Adding or removing a field You can add a field to a visual by choosing it on the **Fields list** pane. You can also drag it to a drop target on the visual or to a field well. There is a 1:1 correspondence of drop targets to field wells for each visual type, so you can use either method. On some charts, the **Axis title** field is hidden when there are two or more fields in the **Value** field on any side of the chart. This effect can happen with the following charts: + Bar charts + Line charts + Box plots + Combo charts + Waterfall charts To remove a field from a visual, clear selection from it in the **Fields list** pane. Or choose an on-visual editor or field well that uses that field, and then choose **Remove** from the context (right-click) menu. ## Adding a field by selecting it in the fields list pane You can also let Amazon Quick map the field to the most appropriate visual element. To do so, choose the field in the **Fields list** pane. Amazon Quick adds the field to the visual by populating the first empty field well that corresponds with that field type (either measure or dimension). If all of the visual elements are already populated, Amazon Quick determines the most appropriate field well and replaces the field in it with the field you selected. ## Adding a field by using a drop target To add a field to a visual by using a drop target, first choose a field in the **Fields list** pane. Then drag the field to your chosen drop target on the visual, making sure the drop indicator shows that the field is being added. ## Adding a field by using a field well To add a field to a visual by using a field well, choose a field in the **Fields list** pane. Then drag the field to the target field well, making sure that the drop indicator shows that the field is being added. 1. Drag a field item into a **Field well**. 1. Drag the field that you want to add from the **Fields list** pane to the appropriate field well. **Note** You can add the same value to the same visual multiple times. You can do so to show the same value with different aggregations or table calculations applied. By default, the fields all display the same label. You can edit the names by using the **Properties** panel, which you open by choosing the **V**-shaped icon at top right. # Changing the field associated with a visual element You can change the field assigned to an element in a visual by using the field wells, drop targets, or the on-visual editors on the visual. For pivot tables, use field wells or drop targets because this visual type doesn't provide on-visual editors. ## Change a field mapping by using an on-visual editor Use the following procedure to modify the mapping of a field to a visual element. **To modify the mapping of a field by using an on-visual editor** 1. On the visual, choose the on-visual editor for the visual element for which you want to change the field. 1. On the on-visual editor menu, choose the field that you want to associate with that visual element. ## Changing a field mapping by using a drop target To modify the mapping of a field to a visual element by using a drop target, choose a field in the **Fields list** pane. Then drag the field to a drop target on the visual, making sure that the drop indicator shows that the field is being replaced. ## Changing a field mapping by using a field well Use the following procedure to modify the mapping of a field to a visual element. **To modify the mapping of a field by using a field well** 1. Drag a field item into a **Field well**. 1. Choose the field well that represents the element that you want to remap, and then choose a new field from the menu that appears. # Changing field aggregation You can apply functions to fields to display aggregate information, like the sum of the sales for a given product. You can apply an aggregate function by using the options in either an on-visual editor or a field well. The following aggregate functions are available in Amazon Quick: + Average – Calculates the average value for the selected field. + Count – Provides a count of the number of records containing the selected measure for a given dimension. An example is a count of Order ID by State. + Distinct Count – Provides a count of how many different values are in the selected measure, for the selected dimension or dimensions. An example is a count of Product by Region. A simple count can show how many products are sold for each region. A distinct count can show how many different products are sold for each region. You might have sold 2,000 items, but only two different types of items. + Max – Calculates the maximum value for the selected field. + Min – Calculates the minimum value for the selected field. + Median – Calculates the median value of the specified measure, grouped by the chosen dimension or dimensions. + Sum – Totals all of the values for the selected field. + Standard Deviation – Calculates the standard deviation of the set of numbers in the specified measure, grouped by the chosen dimension or dimensions, based on a sample or on a biased population. + Variance – Calculates the variance of the set of numbers in the specified measure, grouped by the chosen dimension or dimensions, based on a sample or on a biased population. + Percentile – Computes the *n*th percentile of the specified measure, grouped by the chosen dimension or dimensions. All aggregate functions can be applied to numeric fields. *Count* is automatically applied to a dimension if you choose to use it in a field well that expects a measure. If you have used a dimension in that way, you can also change the aggregate function applied to it. You can't apply aggregate functions to fields in dimension field wells. The visual elements that support aggregated fields varies by visual type. ## Changing or adding aggregation on a field by using an on-visual editor Use the following procedure to change or add aggregation on a field. **To change or add aggregation on a field** 1. On the visual, choose the on-visual editor for the field that you want to apply aggregation to. 1. On the on-visual editor menu, choose **Aggregate**, then choose the aggregate function that you want to apply. ## Changing or adding aggregation to a field by using a field well Use the following procedure to add aggregation to a field for a pivot table visual. **To add aggregation to a field for a pivot table visual** 1. Drag a field item into a **Field well**. 1. Choose the field well containing the field that you want to apply an aggregate function to. 1. On the field well menu, choose **Aggregate**, then choose the aggregate function that you want to apply. # Changing date field granularity You can change the granularity for a date field on a visual to determine the intervals for which item values are shown. You can set the date field granularity to one of the following values: + Year + Quarter + Month + Week + Day (this is the default) + Hour + Minute + Second Hour and minute are available only if the field contains time data. ## Changing date field granularity by using an on-visual editor Use the following procedure to change date field granularity by using an on-visual editor. **To change date field granularity with an on-visual editor** 1. On the visual, choose the field well for the date field whose granularity you want to change. 1. On the field well menu, choose **Aggregate**, then choose the time interval that you want to apply, as shown following: ## Changing date field granularity by using a field well Use the following procedure to change date field granularity by using a field well. **To change date field granularity with a field well** 1. Drag a field item into a **Field well**. 1. Choose the field well containing the date field, and then choose **Aggregate**. Choose the date granularity that you want to use. # Customizing a field format Field format Use the following procedure to customize the appearance of fields in an analysis. **To customize the appearance of fields in an analysis** 1. In an analysis, choose a field to format, either by choosing it in the field well or in the **Fields list** of the **Visualize **pane. 1. Choose **Show as** to change how the field shows in the analysis, and choose from the options on the context menu. The list of available options varies based on the field's data type. If you choose a non-numeric field from the fields list, you can change the *count format*, which is the formatting used when the field is counted. 1. Choose **Format** to change the format of the field, and choose from the options on the context menu. If you don't see an option that you want to use, choose **More formatting options** from the context menu. The **Format Data** pane opens, presenting options for the type of numeric or date field you chose. The options for **Show as** from the context menu now appear in the drop-down list at the top of the **Format Data** pane. The rest of the options are specific to the data type and how you choose to show the field. For date and time data, the default format pattern is YYYY-MM-DD**`T`**HH:mm:ssZZ, for example 2016-09-22T17:00:00-07:00. For numbers, you can choose from the following units to display after the number: + No unit suffix. This is the default. + Thousands (K) + Millions (M) + Billions (B) + Trillions (T) + A custom unit prefix or suffix For currency, you can choose from the following symbols: + Dollars (\$1) + Euros (€) + Pounds (£) + Yen (¥) # Changing a field format You can change the format of a field within the context of an analysis. The formatting options available for fields vary based on the field's data type. Use menu options in the **Field list** pane or the visual field wells to make simple format changes, or use the **Format data** pane to make more extensive formatting changes. **Topics** + [ # Format a currency field ](format-a-currency-field.md) + [ # Format a date field ](format-a-date-field.md) + [ # Format a number field ](format-a-number-field.md) + [ # Format a percent field ](format-a-percent-field.md) + [ # Format a text field ](format-a-text-field.md) + [ # Return a field's format to default settings ](set-field-format-to-default.md) # Format a currency field When you format a currency field, you can either choose the currency symbol from a list of common options, or open the **Format data** pane and manually format the field. Manually formatting the field allows you to choose which symbol to use, which separators to use, the number of decimal places to show, which units to use, and how to display negative numbers. Changing a field format changes it for all visuals in the analysis, but does not change it in the underlying dataset. If you want to choose the symbol for a currency field from a list of common options, you can access such a list in several ways. You can access it from the **Field list** pane, an on-visual editor, or a visual field well. **To select a currency field's symbol by choosing a list option** 1. Choose one of the following options: + In the **Field list** pane, choose the selector icon to the right of the number field that you want to format. + On any visual that contains an on-visual editor associated with the currency field that you want to format, choose that on-visual editor. Expand the **Field wells** pane, and then choose the field well associated with the number field that you want to change. 1. Choose **Format**, and then choose the currency field that you want: + Display in dollars (\$1). + Display in pounds (£). + Display in euros (€). + Display in yen or yuan (¥). **To manually change a currency field's format** 1. Choose one of the following options: + In the **Field list** pane, choose the selector icon to the right of the number field that you want to format. + On any visual that contains an on-visual editor associated with the number field that you want to format, choose that on-visual editor. Expand the **Field wells** pane, and then choose the field well associated with the number field that you want to change. 1. Choose **Format**, and then choose **More Formatting Options**. The **Format data** pane opens. 1. Expand the **Symbol** section and choose from the following options: + Display in dollars (\$1). This is the default. + Display in pounds (£). + Display in euros (€). + Display in yen or yuan (¥). 1. Expand the **Separators** section and choose from the following options: + Under **Decimal**, choose a dot or a comma for the decimal separator. A dot is the default. If you choose a comma instead, use a dot or a space as the thousands separator. + Under **Thousands**, select or clear **Enabled** to indicate whether you want to use a thousands separator. **Enabled** is selected by default. + If you are using a thousands separator, choose whether to use a comma, dot, or space for the separator. A comma is the default. If you choose a dot instead, use a comma as the decimal separator. 1. Expand the **Decimal Places** section and choose the number of decimal places to use. The default is 2. Field values are rounded to the decimal places specified. For example, if you specify two decimal places, the value 6.728 is rounded to 6.73. 1. Expand the **Units** section and choose from the following options: + Choose the unit to use. Choosing a unit adds the appropriate suffix to the number value. For example, if you choose **Thousands**, a field value of 1234 displays as 1.234K. The unit options are as follows: + No unit suffix. This is the default. + Thousands (K) + Millions (M) + Billions (B) + Trillions (T) + If you want to use a custom prefix or suffix, specify it in the **Prefix** or **Suffix** box. Using a custom suffix is a good way to specify a currency suffix outside of those already offered by Amazon Quick. You can specify both. You can also specify a custom prefix in addition to the suffix added by selecting a unit. 1. Expand the **Negatives** section and choose whether to display a negative value by using a minus sign or by enclosing it in parentheses. Using a minus sign is the default. 1. Expand the **Null values** section and choose whether to display null values as `null` or as a custom value. Using `null` is the default. **Note** When using a table or pivot table, null values only display for fields that are placed in the **Rows**, **Columns**, or **Group by** field wells. Null values for fields in the **Values** field well appear empty in the table or pivot table. # Format a date field When you format a date field, you can choose a list of common formatting options. Or you can open the **Format data** pane to choose from a list of common formats, or specify custom formatting for the date and time values. Changing a field format changes it for all visuals in the analysis that use that dataset, but does not change it in the dataset itself. If you want to format a date field by choosing from a list of common options, you can access such a list in several ways. You can access it from the **Field list** pane, a visual on-visual editor, or a visual field well. **To change a date field's format by choosing a list option** 1. Choose one of the following options: + In the **Field list** pane, choose the selector icon to the right of the number field that you want to format. + On any visual that contains an on-visual editor associated with the number field that you want to format, choose that on-visual editor. Expand the **Field wells** pane, and then choose the field well associated with the number field that you want to change. 1. Choose **Format**, and then choose the format that you want. The following quick formatting options are offered for date fields: + Show the month, day, year, and time. + Show the month, day, and year. + Show the month and year. + Show the year. **To manually change a date field's format** 1. Choose one of the following options: + In the **Field list** pane, choose the selector icon to the right of the number field that you want to format. + On any visual that contains an on-visual editor associated with the number field that you want to format, choose that on-visual editor. Expand the **Field wells** pane, and then choose the field well associated with the number field that you want to change. 1. Choose **Format**, and then choose **More Formatting Options**. The **Format data** pane opens. 1. Expand the **Date** section. Choose an existing date format, or choose **Custom** and specify a format pattern in the **Custom** section lower down in the **Format data** pane. If you choose **Custom** for the **Date** section, you must also choose **Custom** for the following **Time** section. The pattern that you specify in the **Custom** section must include any date and time formatting that you want. The default selection is **Custom**, with a default format pattern of MMM D, YYYY h:mma, for example Sep 20, 2022 5:30pm. 1. Expand the **Time** section. Choose an existing time format, or choose **Custom** and specify a format pattern in the **Custom** section lower down in the **Format data** pane. If you choose **Custom** for the **Time** section, you must also choose **Custom** for the preceding **Date** section. The pattern that you specify in the **Custom** section must include any date and time formatting that you want. The default selection is **Custom**, with a default format pattern of MMM D, YYYY h:mma, for example Sep 20, 2022 5:30pm. 1. If you chose **Custom** in the **Date** and **Time** sections, expand the **Custom** section and specify the format pattern that you want, using the format pattern syntax specified in [Moment.js Display Format](https://momentjs.com/docs/#/displaying/) in the Moment.js JavaScript documentation. **Note** The time zone related display token `Z` from the Moment.js library is supported in Quick, but the `z` token is not. If you chose something other than **Custom** in the **Date** and **Time** sections, **Custom** is populated with the format pattern that reflects your selections. For example, if you chose Jun 21, 2016 in the **Date** section and 17:00:00pm in the **Time** section, the **Custom** section shows the format pattern MMM D, YYYY H:mm:ssa. 1. (Optional) Expand the **Custom** section and use **Preview** to verify your specified format. 1. Expand the **Null values** section and choose whether to display null values as `null` or as a custom value. Using `null` is the default. # Customizing date formats in Quick Customizing date formats In Quick, you can customize how dates are formatted in your filter and parameter controls. For example, you can specify to format the date in a control as 20-09-2021, or, if you'd rather, as 09-20-2021. You can also specify to shorten the month in your dates (such as September) to three letters (Sep), among other customizations. Following is a list of tokens you can use to create custom date formats. You can use them in combination with one another to control how dates appear in your controls. ## List of supported tokens for formatting dates Use the following tokens to customize the format of dates in Quick. | Example | Description | Token | | --- | --- | --- | | 0–6 | Numeric representation of a particular day of the week. 0 is Sunday and 6 is Saturday. | `d` | | Mo–Su | A 2-character textual representation of a particular day of the week. | `dd` | | Mon–Sun | A 3-character textual representation of a particular day of the week. | `ddd` | | Monday–Sunday | A textual representation of a particular day of the week. | `dddd` | | 99 or 21 | A 2-digit representation of a year. | `YY` | | 1999 or 2021 | A full, 4-digit numeric representation of a year. | `YYYY` | | 1–12 | Number of a month, without leading zeros. | `M` | | 1st, 2nd, to 12th | Number of a month without leading zeros and with an ordinal suffix. | `Mo` | | 01–12 | Number of a month with leading zeros. | `MM` | | Jan–Dec | A 3-digit textual representation of a month. | `MMM` | | January–December | A full textual representation of a month. | `MMMM` | | 1–4 | A numeric representation of a quarter. | `Q` | | 1st–4th | A numeric representation of a quarter with an ordinal suffix. | `Qo` | | 1–31 | Day of the month without leading zeros. | `D` | | 1st, 2nd, to 31st | Day of the month without leading zeros and an ordinal suffix. | `Do` | | 01–31 | A 2-digit day of the month with leading zeros. | `DD` | | 1–365 | Day of the year without leading zeros. | `DDD` | | 001–365 | Day of the year with leading zeros. | `DDDD` | | 1–53 | Week of the year without leading zeros. | `w` | | 1st–53rd | The week of the year without leading zeros and with an ordinal suffix. | `wo` | | 01–53rd | Week of the year with leading zeros. | `ww` | | 1–23 | Hours, in 24-hour format, without leading zeros. | `H` | | 01–23 | Hours, in 24-hour format, with leading zeros. | `HH` | | 1–12 | Hours, in 12-hour format, without leading zeros. | `h` | | 01–12 | Hours, in 12-hour format, with leading zeros. | `hh` | | 0–59 | Minutes without leading zeros. | `m` | | 00–59 | Minutes with leading zeros. | `mm` | | 0–59 | Seconds without leading zeros. | `s` | | 00–59 | Seconds with leading zeros. | `ss` | | am or pm | am/pm | `a` | | AM or PM | AM/PM | `A` | | 1632184215 | Unix timestamp. | `X` | | 1632184215000 | Millisecond Unix timestamp. | `x` | | Z | Zero UTC offset. | `Z` | The following date types are not supported. + Time zones offset with a colon. For example, \$107:00. + Time zones offset without a colon. For example, \$10730. ### Preset date formats To quickly customize dates and times to appear as one of the following example formats, you can use the following Quick preset tokens. | Example | Token | | --- | --- | | 8:30 PM | `LT` | | 8:30:25 PM | `LTS` | | August 2 1985 | `LL` | | Aug 2 1985 | `ll` | | August 2 1985 08:30 PM | `LLL` | | Aug 2 1985 08:30 PM | `lll` | | Thursday, August 2 1985 08:30 PM | `LLLL` | | Thu, Aug 2 1985 08:30 PM | `llll` | ## Common date formats Following are three common date examples and their associated token formats for your quick reference. | Example | Token Format | | --- | --- | | Sep 20, 2021 | `MMM DD, YYYY` | | 20-09-21 5pm | `DD-MM-YY ha` | | Monday, September 20, 2021 17:30:15 | `dddd, MMMM DD, YYYY HH:mm:ss` | ## Adding words to dates To include words in your date formats, such as the word "of" in *20th of Sep, 2021*, enter backslashes (\$1) before each character in the word. For example, for the 20th of Sep, 2021 date example, use the following token format: `Do \o\f MMM, YYYY`. ## Example: Customizing the date format in a filter control Customizing the date format in a filter control Use the following procedure to learn how to use date token formats to customize dates for a filter control. **To learn to customize dates for a filter control with data tokens** 1. In a Quick analysis, choose the filter control that you want to customize. 1. On the filter control, choose the **Edit control** icon. 1. On the **Edit control** page that opens, for **Date format**, enter the custom date format that you want. Use the tokens listed previously in this topic. For example, let's say that you want to customize your dates using the following format: *Sep 3rd, 2020 at 5pm*. To do so, you can enter the following token format: `MMM Do, YYYY \a\t ha` A preview of the date format appears below the input field as you enter each token. 1. Choose **Apply**. The dates in the control update to the format you specified. # Format a number field When you format a number field, you can choose the decimal place and thousand separator format from a list of common options. Or you can open the **Format Data** pane and manually format the field. Manually formatting the field enables you to choose which separators to use and the number of decimal places to show. It also enables you to choose which units to use, and how to display negative numbers. Changing a field format changes it for all visuals in the analysis, but does not change it in the underlying dataset. If you want to format a number field by choosing from a list of common options, you can access such a list from the **Field list** pane, an on-visual editor, or a visual field well. **To change a number field's format by choosing a list option:** + Choose one of the following options: + In the **Field list** pane, choose the selector icon to the right of the number field that you want to format. + On any visual that contains an on-visual editor associated with the number field that you want to format, choose that on-visual editor. Expand the **Field wells** pane, and then choose the field well associated with the number field that you want to change. + Choose **Format**, and then choose the format that you want. The following quick formatting options are offered for number fields: + Use commas to separate groups of thousands and use a decimal point to show the fractional part of the number, for example 1,234.56. + Use a decimal point to show the fractional part of the number, for example 1234.56. + Show the number as an integer and use commas to separate groups of thousands, for example 1,234. + Show the number as an integer, for example 1234. **To manually change a number field's format:** 1. Choose one of the following options: + In the **Field list** pane, choose the selector icon to the right of the number field that you want to format. + On any visual that contains an on-visual editor associated with the number field that you want to format, choose that on-visual editor. Expand the **Field wells** pane, and then choose the field well associated with the number field that you want to change. 1. Choose **Format**, and then choose **More Formatting Options**. The **Format data** pane opens. 1. Expand the **Separators** section and choose from the following options: + Under **Decimal**, choose a dot or a comma for the decimal separator. A dot is the default. If you choose a comma instead, use a dot or a space as the thousands separator. + Under **Thousands**, select or clear **Enabled** to indicate whether you want to use a thousands separator. **Enabled** is selected by default. + If you are using a thousands separator, choose whether to use a comma, dot, or space for the separator. A comma is the default. If you choose a dot instead, use a comma as the decimal separator. 1. Expand the **Decimal Places** section and choose from the following options: + Choose **Auto** to have Amazon Quick automatically determine the appropriate number of decimal places, or choose **Custom** to specify a number of decimal places. **Auto** is the default. + If you chose **Custom**, enter the number of decimal places to use. Field values are rounded to the decimal places specified. For example, if you specify two decimal places, the value 6.728 is rounded to 6.73. 1. Expand the **Units** section and choose from the following options: + Choose the unit to use. Choosing a unit adds the appropriate suffix to the number value. For example, if you choose **Thousands**, a field value of 1234 displays as 1.234K. The unit options are as follows: + No unit suffix. This is the default. + Thousands (K) + Millions (M) + Billions (B) + Trillions (T) + If you want to use a custom prefix or suffix, specify it in the **Prefix** or **Suffix** box. You can specify both. You can also specify a custom prefix in addition to the suffix added by selecting a unit. 1. Expand the **Negatives** section and choose whether to display a negative value by using a minus sign or by enclosing it in parentheses. Using a minus sign is the default. 1. Expand the **Null values** section and choose whether to display null values as `null` or as a custom value. Using `null` is the default. **Note** When using a table or pivot table, null values only display for fields that are placed in the **Rows**, **Columns**, or **Group by** field wells. Null values for fields in the **Values** field well appear empty in the table or pivot table. # Format a percent field When you format a percent field, you can choose the number of decimal places from a list of common options. Or you can open the **Format data** pane and manually format the field. Manually formatting the field enables you to choose which separators to use. It also enables you to choose the number of decimal places to show and how to display negative numbers. Changing a field format changes it for all visuals in the analysis, but does not change it in the underlying dataset. If you want to choose the number of decimal places for a percent field from a list of common options, you can access such a list in several ways. You can access it from the **Field list** pane, an on-visual editor, or a visual field well. **To change a percent field's number of decimal places by choosing a list option** 1. Choose one of the following options: + In the **Field list** pane, choose the selector icon to the right of the number field that you want to format. + On any visual that contains an on-visual editor associated with the percent field that you want to format, choose that on-visual editor. Expand the **Field wells** pane, and then choose the field well associated with the number field that you want to change. 1. Choose **Format**, and then choose the number of decimal places that you want. The following quick formats are offered for percent fields: + Display the value with two decimal places. + Display the value with one decimal place. + Display the value with no decimal places. **To manually change a percent field's format** 1. Choose one of the following options: + In the **Field list** pane, choose the selector icon to the right of the number field that you want to format. + On any visual that contains an on-visual editor associated with the number field that you want to format, choose that on-visual editor. Expand the **Field wells** pane, and then choose the field well associated with the number field that you want to change. 1. Choose **Format**, and then choose **More Formatting Options**. The **Format data** pane opens. 1. Expand the **Separators** section and choose from the following options: + Under **Decimal**, choose a dot or a comma for the decimal separator. A dot is the default. If you choose a comma instead, use a dot or a space as the thousands separator. + Under **Thousands**, select or clear **Enabled** to indicate whether you want to use a thousands separator. **Enabled** is selected by default. + If you are using a thousands separator, choose whether to use a comma, dot, or space for the separator. A comma is the default. If you choose a dot instead, use a comma as the decimal separator. 1. Expand the **Decimal Places** section and choose from the following options: + Choose **Auto** to have Amazon Quick automatically determine the appropriate number of decimal places, or choose **Custom** to specify a number of decimal places. **Auto** is the default. + If you chose **Custom**, enter the number of decimal places to use. Field values are rounded to the decimal places specified. For example, if you specify two decimal places, the value 6.728 is rounded to 6.73. 1. Expand the **Negatives** section and choose whether to display a negative value by using a minus sign or by enclosing it in parentheses. Using a minus sign is the default. 1. Expand the **Null values** section and choose whether to display null values as `null` or as a custom value. Using `null` is the default. **Note** When using a table or pivot table, null values only display for fields that are placed in the **Rows**, **Columns**, or **Group by** field wells. Null values for fields in the **Values** field well appear empty in the table or pivot table. # Format a text field When you format a text field, you can choose how to display null values using the **Field list** pane, an on-visual editor, or a visual field well. **To choose how to display a text field's null values** 1. Choose one of the following options: + In the **Field list** pane, choose the selector icon to the right of the number field that you want to format. + On any visual that contains an on-visual editor associated with the percent field that you want to format, choose that on-visual editor. Expand the **Field wells** pane, and then choose the field well associated with the number field that you want to change. 1. Choose **Format**, and then choose **More Formatting Options**. The **Format data** pane opens. 1. Expand the **Null values** section and choose whether to display null values as `null` or as a custom value. Using `null` is the default. # Return a field's format to default settings Use the following procedure to return a field's format to the default settings. **To return a field's format to the default settings** 1. In the **Field list** pane, choose the selector icon to the right of the field that you want to reset. 1. Choose **Format**, and then choose **More Formatting options**. The **Format data** pane opens. 1. Choose **Reset to defaults**. # Sorting visual data in Amazon Quick Sorting visual data You can sort data using multiple methods for most visual types. You can choose the sort order of on-visual data by using the quick sort option or field wells. You can also use field wells to sort data by an off-visual metric. The visual element you can sort by depends on the visual type and whether sorting is supported for that visual. For more information on which visual types support sorting, see [Analytics formatting per type in Quick](analytics-format-options.md). Pivot tables behave differently than tables when sorting values. For more information about sorting pivot tables, see [Sorting pivot tables in Quick](sorting-pivot-tables.md). For SPICE datasets, you can sort text strings of sizes up to the following limitations: + Up to two million (2,000,000) unique values + Up to 16 columns When you exceed the limitations, the visual displays a notification at the upper right. You can sort any visual type that supports sorting. If a visual type supports sorting, you can sort by using either the quick sort option or a field well. **To quickly sort dimensions and measures** + Do one of the following: + Choose the sort icon that appears near the field name on either axis. In direct queries, this icon appears for any data type. For SPICE, this icon is available only for datetime, numeric, and decimal data types. + Choose the field name and then choose the sort option from the menu. If the label doesn't display on the axis, check the visual format to see if the axis is set to display labels. The display labels are automatically hidden on smaller visuals. You might need to make the visual large enough to display labels. **To sort by using an off-visual metric** 1. Open the analysis with the visual that you want to sort. Visuals pane will be open by default. 1. Choose a field well that supports sorting, then choose **Sort by**, **Sort options**. 1. On the **Sort options** pane, sort by specific fields, choose an aggregation, or sort ascending or descending, or do a combination of these. 1. Choose **Apply** to save your changes. Or choose **Clear** to start over or **Cancel** to go back. **To sort by using a field well** 1. Open the analysis with the visual that you want to sort. Visuals pane will be open by default. 1. Choose a field well that supports sorting. 1. On the field well menu, choose **Sort**, and then choose the ascending or descending sort order icon.