---
title: Lens
description: Lens is Kibana's modern, drag‑and‑drop visualization editor designed to make data exploration fast and intuitive. It allows you to build charts and tables...
url: https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/lens
products:
- Kibana
applies_to:
- Elastic Cloud Serverless: Generally available
- Elastic Stack: Generally available
---
# Lens
**Lens** is Kibana's modern, drag‑and‑drop visualization editor designed to make data exploration fast and intuitive. It allows you to build charts and tables by dragging fields from a data view onto a workspace, while Kibana automatically suggests the most appropriate visualization types based on the data.
The Lens editor uses [data views](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/find-and-organize/data-views) to define the available Elasticsearch indices and fields.
Data views are created automatically if you [upload a file](https://www.elastic.co/elastic/docs-builder/docs/3028/manage-data/ingest/upload-data-files), or [add sample data](https://www.elastic.co/elastic/docs-builder/docs/3028/manage-data/ingest/sample-data) by using one of the Kibana [ingest options](https://www.elastic.co/elastic/docs-builder/docs/3028/manage-data/ingest). Otherwise, you must create a data view manually.
Once you select a data view, you can build many types of visualizations by choosing aggregations, splitting dimensions, and configuring chart styles, legends, and layers.
A skill is available to help AI agents with this topic.
With Lens, you can create the following visualization types:
| **Chart type** | **Use when you want to...** |
|------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------|
| **XY charts** | **Plot data on axes to reveal trends, comparisons, and distributions.** |
| [Bar](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/bar-charts) | Compare values across discrete categories or show distributions with histogram buckets. |
| [Line](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/line-charts) | Show how a metric changes over time or another continuous dimension. |
| [Area](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/area-charts) | Show change over time while emphasizing volume or stacked proportions. |
| **Partition charts** | **Divide a total into segments to show how parts relate to the whole.** |
| [Pie](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/pie-charts) | Show how parts make up a whole with a small number of slices. |
| [Treemap](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/treemap-charts) | Show hierarchical proportions across nested categories. |
| [Waffle](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/waffle-charts) | Show part-to-whole as a grid of equal cells where filled cells represent proportion. |
| [Mosaic](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/mosaic-charts) | Compare part-to-whole across two categorical dimensions in a tiled layout. |
| **Single value charts** | **Highlight a key number, KPI, or progress toward a goal.** |
| [Metric](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/metric-charts) | Highlight a single KPI or a small set of critical numbers. |
| [Gauge](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/gauge-charts) | Show progress toward a target or status against thresholds for a single metric. |
| **More charts** | **Additional visualizations for tabular data, spatial patterns, and text analysis.** |
| [Table](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/tables) | Present precise values, rankings, or multi-metric details in a compact layout. |
| [Heat map](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/heat-map-charts) | Reveal density or patterns across two dimensions using color intensity. |
| [Tag cloud](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/tag-cloud-charts) | Highlight the most frequent or important terms in a dataset. |
| [Region map](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/region-map-charts) | Show how values vary across geographic regions (choropleth). |
## Create visualizations
If you’re unsure about the visualization type you want to use, or how you want to display the data, drag the fields you want to visualize onto the workspace, then let **Lens** choose for you.
If you already know the visualization type you want to use, and how you want to display the data, use the following process.
New visualizations default to **Bar** charts. Use the dropdown indicating **Bar** and select the visualization type you want.
As you drag fields into the workspace or to the layer pane, Lens automatically generates alternative visualizations. To view them, click **Suggestions** at the bottom of the workspace. If a suggested visualization meets your needs, click **Save and return** to add it to the dashboard.
As you drag fields to the layer pane, Lens automatically selects an aggregation function, for example **Date histogram**, **Intervals**, or **Top values**. Click a field to learn more about its data or to edit its appearance.
In the Lens editor, you can customize the appearance of your visualization by clicking the **Style** icon `brush` and the **Legend** icon  in the layer pane.
You can add multiple layers to a visualization, such as **Visualization**, [**Annotations**](#add-annotations), or [**Reference lines**](#add-reference-lines). Click the **Add layer** icon `plus_in_square` , then choose the layer type and select the data view.
To duplicate or delete a layer, click  on the layer tab.
- If you accessed Lens from a dashboard, select **Save and return** to save the visualization and add it to that dashboard, or select **Save to library** to add the visualization to the Visualize library and reuse it later.
- If you accessed Lens from the Visualize library, select **Save**. A menu opens and lets you add the visualization to a dashboard and to the Visualize library.
Once you have created your visualization, you can edit it directly on the dashboard. Click the **Edit visualization configuration** icon  on the panel.
### Change the fields list
When you can create a visualization, you can change the fields list to display a different data view, a different time range, or add your own fields. To do that, open the data view dropdown and select **Add a field to this data view**.
If the fields list is empty, change the [time filter](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/query-filter/filtering).
For more information about adding fields to data views and examples, refer to [Explore your data with runtime fields](/elastic/docs-builder/docs/3028/explore-analyze/find-and-organize/data-views#runtime-fields).
### Assign colors to terms
- Elastic Cloud Serverless: Generally available
- Elastic Stack: Generally available since 9.1
- Elastic Stack: Preview in 9.0
You can assign specific colors to terms in your visualizations. This color mapping can be useful in several situations:
- **Visual recognition and recall**: Keep colors consistent for each term regardless of filters or sorting.
- **Semantic meaning**: Use colors to convey meaning or categorization.
- **Consistency**: Align with brand colors and improve overall aesthetic consistency.
#### Supported visualization types
Color mapping is available for the following **Lens** visualization types:
- **Data tables**: Assign colors to terms in **Rows** or **Metrics** fields. You can apply colors to cell backgrounds or text.
- **XY charts (Area, Bar, Line)**: Assign colors to breakdown dimensions that split your data into multiple series.
- **Partition charts (Donut, Pie, Treemap, Waffle)**: Assign colors to the main slice or group-by dimension that defines the chart segments.
- **Tag clouds**: Assign colors to the tags dimension that determines the terms displayed in the cloud.
#### Configure color mapping in a chart
To assign colors to terms in your visualization:
1. Create a visualization using one of the supported types.
2. Add a categorical field that contains the terms you want to color.
3. In the field configuration, look for the **Color by value** option:
- For data tables: Select **Cell** or **Text**
- For other chart types: This option appears when you have a categorical breakdown
4. Click the **Edit colors** icon. In the menu that opens, keep **Use legacy palettes** turned off to be able to assign colors to specific terms
5. Select a color palette from the available options:
- **Elastic**: The default and most recent palette. It is intentionally built from a color spectrum designed for flexibility and consistency, while being suited for future accessibility improvements.
- **Kibana 7.0**: A palette that matches the Kibana 7.0 color theme for visualizations
- **Kibana 4.0**: A palette that matches the Kibana 4.0 color theme for visualizations
- **Elastic classic**: A palette made of classic Elastic brand colors
6. Select the color mode you'd like to use with this palette:
- **Categorical**: Assign a distinct color to each term
- **Gradient**: Assign gradients of the same color to each term
7. Choose which terms to color. You can assign colors manually or select **Add all unassigned terms** for automatic assignment.
You can assign several terms to the same color.
8. Choose how to handle unassigned terms: Use the selected color palette or assign a single color.
#### Color options and accessibility
**Discrete colors and gradients**
Choose from discrete color sets or generate sequential or divergent gradients. Gradients work well for Likert scales and other term scales.
**Theme-aware neutral colors**
Use neutral gray colors that adjust automatically between light and dark themes. These help de-emphasize less important data.
**Accessibility warnings**
The system warns you when colors don't have enough contrast for accessibility.
#### Best practices
**Maintain consistency**
Use color mapping to create consistent color schemes when the same categorical data appears across multiple visualizations in your dashboards.
**Use semantic colors**
Leverage color associations that users already understand (such as red for errors, green for success) to make your visualizations more intuitive.
**Consider performance**
Color mapping works best with fields that have a reasonable number of distinct values. Fields with hundreds or thousands of unique terms may impact visualization performance.
**Plan for themes**
When choosing colors, consider how they appear in both light and dark themes. Use theme-aware neutral colors when you want to de-emphasize data.
### Create visualizations with keyboard navigation
To use a keyboard instead of a mouse, use the **Lens** fully accessible and continuously improved drag system.
1. Select the field in the fields list or layer pane. Most fields have an inner and outer select state. The inner state opens a panel with detailed information or options. The outer state allows you to drag the field. Tab through the fields until you get the outer state on the field.
2. Complete the following actions:
- To select a field, press Space bar.
- To select where you want to drop the field, use the Left and Right arrows.
- To reorder the fields on the layer pane, use the Up and Down arrows.
- To duplicate an action, use the Left and Right arrows, then select the **Drop a field or click to add** field you want to use.
3. To confirm the action, press Space bar. To cancel, press Esc.
### Use formulas to perform math
Lens formulas let you do math using a combination of Elasticsearch aggregations and math functions. For example, you can use formulas to divide two values and produce a percent value.
When you add a categorical field to your visualization, select the field to open its appearance settings, choose **Formula**, and set **Appearance** > **Value format** to **Percent** for a more accurate display.
For more details on how it works, click the **Formula reference** icon  on the Formula panel.
These are examples of common formulas:
To filter a document set, use `kql=''`, then compare to other documents within the same grouping:
```
count(kql='response.status_code > 400') / count()
```
To get the value for each grouping from the previous week, use `shift='1w'`.
```
percentile(system.network.in.bytes, percentile=99) /
percentile(system.network.in.bytes, percentile=99, shift='1w')
```
You are unable to combine different time shifts, such as `count(shift="1w") - count()` and `count(shift="1w") - count(shift="1m")`, with the **Top values** function.
To convert each grouping into a percent of the total, formulas calculate `overall_sum` for all groupings:
```
sum(products.base_price) / overall_sum(sum(products.base_price))
```
### Compare differences over time
Compare your real-time data to the results that are offset by a time increment. For example, you can compare the real-time percentage of a user CPU time spent to the results offset by one hour.
1. In the layer pane, click the field you want to offset.
2. Click **Advanced**.
3. In the **Time shift** field, enter the time offset increment.
For a time shift example, refer to [Compare time ranges](/elastic/docs-builder/docs/3028/explore-analyze/dashboards/create-dashboard-of-panels-with-ecommerce-data#compare-time-ranges).
### Create partition charts with multiple metrics
To create partition charts, such as pie charts, configure one or more **Slice by** dimensions to define the partitions, and a **Metric** dimension to define the size. To create partition charts with multiple metrics, use the layer settings. Multiple metrics are unsupported for mosaic visualizations.
For detailed instructions on creating pie charts, including best practices and configuration options, refer to [Build pie charts with Kibana](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/pie-charts).
1. In the layer pane, click , then select **Layer settings**.
2. Select **Multiple metrics**.
3. Click **X**.
### Improve visualization loading time
- Elastic Stack: Preview
Data sampling allows you to improve the visualization loading time. When you can create your visualization, click the **Layer settings** icon `app_management` and use the slider to adjust the **Sampling** percentage. For example, on large datasets, you can decrease the loading time by using a lower sampling percentage. This increases performance but lowers the accuracy.
### Add annotations
- Elastic Stack: Preview
Annotations allow you to call out specific points in your visualizations that are important, such as significant changes in the data. You can add annotations for any data view, add text and icons, specify the line format and color, and more.
Click the **Add layer** icon `plus_in_square` , select **Annotations** and select the annotation method you want to use:
1. Select the data view for the annotation.
2. From the fields list, drag a field to the **Horizontal axis** field.
To use global filters in the annotation, click the **Layer settings** icon `app_management` on the annotations layer, and select **Use global filters**.From the annotation panel, you can choose the type of placement and adjsut the its appearance.
- **Static date** — Displays annotations for specific times or time ranges. To create static annotations:
1. Select **Static date**.
2. In the **Annotation date** field, click , then select the date.
3. To display the annotation as a time range, select **Apply as range**, then specify the **From** and **To** dates.
- **Custom query** — Displays annotations based on custom Elasticsearch queries. For information about queries, check [Semi-structured search](/elastic/docs-builder/docs/3028/explore-analyze/query-filter/languages/kql#semi-structured-search). To create custom query annotations:
1. Select **Custom query**.
2. Enter the **Annotation query** for the data you want to display. For detailed information about queries and examples, check [Semi-structured search](/elastic/docs-builder/docs/3028/explore-analyze/query-filter/languages/kql#semi-structured-search).
3. Select the **Target date field**.
Configure the annotation settings, including:
- **Name**: Enter the name of the annotation.
- **Icon decoration**: Choose from various icon styles to represent your annotations on the visualization. Options include markers like circles, triangles, squares, and other symbols.
- **Text decoration**: Set the style for the text labels of your annotations.
- **Line**: Control the width/thickness of annotation lines.
- **Color**: Set a custom color for your annotation markers.
- **Hide annotation**: Temporarily hide annotations from your visualization without deleting them.
**Tooltip**
: Add a field to the annotation tooltip
1. If you created a custom query annotation, click **Add field** to add a field to the annotation tooltip.
Once you are done, you can add your new annotation layer to the **Visualize Library** so that it can be reused in other visualizations. Note that any changes made to the annotation group is reflected in all visualizations to which it is added.
Add a library annotation group to a visualization.
### Add reference lines
With reference lines, you can identify specific values in your visualizations with icons, colors, and other display options. You can add reference lines to any visualization type that displays axes.
For example, to track the number of bytes in the 75th percentile, add a shaded **Percentile** reference line to your time series visualization.
From your visualization, click **Add layer > Reference lines**. Click the vertical axis value, and specify the reference line you want to use by choosing one fhe following placement methods:
To add a static reference line.
To add a dynamic reference line.
To calculate the reference line value with math.
You can also customize the display by adjusting the **Appearance** settings.
### Apply filters
You can use the query bar to create queries that filter all the data in a visualization, or use the layer pane and legend filters to apply filters based on field values.
#### Apply multiple KQL filters
With the **Filters** function, you can apply more than one KQL filter, and apply a KQL filter to a single layer so you can visualize filtered and unfiltered data at the same time.
1. In the layer pane, click a field.
2. Click the **Filters** function.
3. Click **Add a filter**, then enter the KQL filter you want to apply.
To try the **Filters** function on your own, refer to [Compare a subset of documents to all documents](/elastic/docs-builder/docs/3028/explore-analyze/dashboards/create-dashboard-of-panels-with-web-server-data#custom-ranges).
#### Apply a single KQL filter
With the **Filter by** advanced option, you can assign a color to each filter group in **Bar** and **Line and area** visualizations, and build complex tables. For example, to display failure rate and the overall data.
1. In the layer pane, click a field.
2. Click **Add advanced options**, then select **Filter by**.
3. Enter the KQL filter you want to apply.
#### Apply legend filters
Apply filters to visualizations directly from the values in the legend. **Bar**, **Line and area**, and **Proportion** visualizations support legend filters.
In the legend, click the field, then choose one of the following options:
- **Filter for value** — Applies a filter that displays only the field data in the visualization.
- **Filter out value** — Applies a filter that removes the field data from the visualization.
#### Filter pill actions
You can interact with filter pills to edit them, temporarily alter their behavior without having to remove them, or make them available in other contexts. The following options are available when selecting a filter pill:
Adds this filter to available dashboards and to apps such as **Discover**, **Lens**, **Maps**, and **Visualize**. You remove the filter if you:
- Unpin it. In this case, the filter only remains on the currently open app, unpinned.
- Remove it from any place while it's still pinned.
- Refresh your session, for example by opening a dashboard in a new tab. Pinned filters are not saved along with the dashboard, visualization, or Discover session that you added them to.
When a pinned filter can't be applied, for example if a field specified in the filter doesn't exist in the current data view, the filter is ignored and shows in a different color.
Lets you edit and update the filter.
Reverses the filter behavior.
Lets you temporarily deactivate a filter instead of requiring you to remove it. This is particularly useful for testing different filter combinations.
Removes the filter.
You can perform most of these actions at once for all filters in your current view using the **Filter** icon `filter`. From the menu that opens, select **Apply to all**, then choose the action you'd like to perform.
## Customize the visualization display
Each visualization offers various options that you can use to customize its appearance:
- **Style** — Specifies how to display area, line, and bar chart options. For example, you can specify how to display the labels in bar charts.
- **Labels** — Specifies how to display the labels for donut charts, pie charts, and treemaps.
- **Legend** — Specifies how to display the legend. You can choose to display the legend inside or outside the visualization, truncate the legend values when they’re too long, and [select additional statistics to show](#customize-visualization-legend).
- **Left axis**, **Bottom axis**, and **Right axis** — Specify how you want to display the chart axes. For example, add axis labels and change the orientation and bounds.
### Visualization appearance and style options
You can customize the appearance of your visualizations with several options. To do that, look for the `brush` **Style** button.
These options can vary depending on the type of chart.
#### Area, Bar, and Line charts
For **Area** charts. Opacity of the area fill. Defaults to `0.3`.
For **Bar** charts. Choose between **Horizontal** and **Vertical**.
For **Line** charts. Choose how to interpolate the line between data points from the available options: **Straight** (default), **Smooth**, and **Step**.
For **Area** and **Line** charts. Choose between **Hide**, **Zero**, **Linear**, **Last**, and **Next**. This option controls how gaps in data appear on the chart. By default, gaps are hidden.
_Missing values_ include empty buckets and metrics: Buckets without documents or metrics that returned `null` due to their operation and data content.
You can only use this option when the **Include empty rows** option of the chart is enabled or when a metric produces a null bucket. For example, if a moving average finds empty buckets.
- **Hide**: Don't show gaps in data.
- **Zero**: Fill gaps by connecting starting and ending data points to zero.
- **Linear**: Fill gaps by connecting related starting and ending data points together with a direct line.
- **Last**: Fill gaps between data points with a horizontal or vertical line that uses the last ending point value, when available, to determine its position.
- **Next**: Fill gaps between data points with a horizontal or vertical line that uses the next starting point value, when available, to determine its position.
If you've chosen to show missing values, you can also decide to extend data series to the edge of the chart. By default, end values are hidden.
- **Hide**: Don't extend series to the edge of the chart.
- **Zero**: Extend series as zero to the edge of the chart.
- **Nearest**: Extend series with their first or last value to the edge of the chart.
If you've chosen to show missing values, you can turn on this option to show gaps as a dotted line.
For **Area** and **Line** charts. Use this option to show or hide data points. Set to `Auto` by default: Points are visible unless the distance between them is too short.
#### Metric charts
- Elastic Stack: Generally available since 9.2
When creating or editing a visualization, you can customize several appearance options. To do that, look for the `brush` **Style** button.
Define the formatting of the primary metric in terms of **Position**, **Alignment**, and **Font size**.
Enter a subtitle and define the relevant **Alignment** and **Font weight**.
Define the **Alignment**.
Choose the **Icon** position.
#### Tables
Make the table more or less compact. Choose between **Compact**, **Normal** (default), and **Expanded**.
The maximum number of lines that header cells can span over. If the content exceeds this limit and is truncated, an ellipsis indicates it.
The fixed number of lines that body cells span over. If the content exceeds this limit and is truncated, an ellipsis indicates it.
Turn on this option to paginate the table. Pagination shows when the table contains at least 10 items, and lets you define how many items to display per page. When turned off, you can scroll through all items.
#### Pie charts
For comprehensive pie chart documentation, including best practices, advanced scenarios, and all configuration options, refer to [Build pie charts with Kibana](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/visualize/charts/pie-charts).
Display a **Small**, **Medium**, or **Large** hole at the center of the pie chart. Defaults to **None**.
#### Gauge charts
Define the shape of the gauge. Choose between **Linear**, **Minor arc**, **Major arc**, and **Circle**. When set to **Linear**, you can choose to display the chart horizontally or vertically.
#### Tag clouds
Define the range of font sizes used in the tag cloud. The font size is based on the number of times a tag appears in the data.
Define the orientation of the tags. Choose **Single**, **Right angled**, and **Multiple**.
Turn on this option to show a label for the tag cloud. You can define this label when defining the tags to show for the visualization, by customizing the **Name** field.
### Customize the visualization legend
To customize the legend of your visualization, click the **Legend** icon  in the layer pane.
The options available can vary based on the type of chart you’re setting up. For example, showing additional statistics is only possible for time series charts.
**Change the legend’s display**
With the **Visibility**, **Position**, and **Width** options, you can adjust the way the legend appears in or next to the visualization.
**Truncate long labels**
With the **Label truncation** option, you can keep your legend minimal in case of long labels that span over multiple lines.
**Show additional statistics for time series charts**
To make your legends as informative as possible, you can show some additional **Statistics** for charts with a timestamp on one of the axes, and add a **Series header**.
**Bar**, **Line** and **Area** charts can show the following values:
- **Average**: Average value considering all data points in the chart
- **Median**: Median value considering all data points in the chart
- **Minimum**: Minimum value considering all data points in the chart
- **Maximum**: Maximum value considering all data points in the chart
- **Range**: Difference between min and max values
- **Last value**: Last value considering all data points in the chart
- **Last non-null value:** Last non-null value
- **First value**: First value considering all data points in the chart
- **First non-null value**: First non-null value
- **Difference**: Difference between first and last values
- **Difference %**: % difference between first and last values
- **Sum**: Sum of al values plotted in the chart
- **Count**: number of data points plotted in the chart
- **Distinct Count**: number of data points with different values plotted in the chart
- **Variance**: Variance of all data points plotted in the chart
- **Std Deviation**: Standard deviation of all data points plotted in the chart
- **Current or last value**: The exact value of the current or last data point moused over
All statistics are computed based on the selected time range and the aggregated data points shown in the chart, rather than the original data coming from Elasticsearch.
For example, if the metric plotted in the chart is `Median(system.memory)` and the time range is **last 24 hours**, when you show the **Max** statistic in the Legend, the value that shows corresponds to the `Max[Median(system.memory)]` for the last 24 hours.
## Explore the data in Discover
When your visualization includes one data view, you can open and explore the visualization data in **Discover**.
To get started, click **Explore data in Discover** in the toolbar.
For more information about exploring your data with **Discover**, check out [Discover](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/discover).
## View the visualization data and requests
To view the data included in the visualization and the requests that collected the data, use the **Inspector**.
1. In the toolbar, click **Inspect**.
2. Open the **View** dropdown, then click **Data**.
1. From the dropdown, select the table that contains the data you want to view.
2. To download the data, click **Download CSV**, then select the format type.
3. Open the **View** dropdown, then click **Requests**.
1. From the dropdown, select the requests you want to view.
2. To view the requests in **Console**, click **Request**, then click **Open in Console**.
## Frequently asked questions
For answers to common **Lens** questions, review the following.
- **Normalize by unit** — Calculates the average for the interval. When you normalize the data by unit, the data appears less granular, but **Lens** is able to calculate the data faster.
- **Customize time interval** — Creates a bucket for each interval. When you customize the time interval, you can use a large time range, but **Lens** calculates the data slower.
To normalize the interval:
1. In the layer pane, click a field.
2. Click **Add advanced options > Normalize by unit**.
3. From the **Normalize by unit** dropdown, select an option, then click **Close**.
To create a custom interval:
1. In the layer pane, click a field.
2. Select **Customize time interval**.
3. Change the **Minimum interval**, then click **Close**.
The **Other** category contains all of the documents that do not match the specified criteria or filters. Use **Other** when you want to compare a value, or multiple values, to a whole.By default, **Group other values as "Other"** is enabled when you use the **Top values** function.To disable **Group other values as "Other"**, click a field in the layer pane, click **Advanced**, then deselect **Group other values as "Other"**.
By default, **Lens** retrieves only the documents from the fields. For bucket aggregations, such as **Top values**, you can add documents that do not contain the fields, which is helpful when you want to make a comparison to the whole documentation set.
1. In the layer pane, click a field.
2. Click **Advanced**, then select **Include documents without this field**.
Use runtime fields to format, concatenate, and extract document-level fields. Runtime fields work across all of Kibana and are best used for smaller computations without compromising performance.Use formulas to compare multiple Elasticsearch aggregations that can be filtered or shifted in time. Formulas apply only to **Lens** panels and are computationally intensive.
For each y-axis, you can select **Left** and **Right**, and configure a different scale.
Here’s a short list of few different aspects to check:
- Make sure the value falls within the desired color stop value defined in the panel. Color stop values are "inclusive".
- Make sure you have the correct value precision setup. Value formatters could round the numeric values up or down.
- Make sure the correct color continuity option is selected. If the number is below the first color stop value, a continuity of type `Below` or `Above and below range` is required.
- The default values set by the Value type are based on the current data range displayed in the data table.
- If a custom `Number` configuration is used, check that the color stop values are covering the current data range.
- If a `Percent` configuration is used, and the data range changes, the colors displayed are affected.
Multiple column sorting is unsupported, but is supported in **Discover**. For information on how to sort multiple columns in **Discover**, refer to [Explore the fields in your data](/elastic/docs-builder/docs/3028/explore-analyze/discover/discover-get-started#explore-fields-in-your-data).
The following field types do not appear in the **Available fields** list:
- Full-text
- geo_point
- flattened
- object
Verify if the field appears in the **Empty fields** list. **Lens** uses heuristics to determine if the fields contain values. For sparse data sets, the heuristics are less precise.
When you create **Area** and **Line** charts with sparse time series data, open **Visual options** in the editor toolbar, then select a **Missing values** option.
You can set the scale, or *bounds*, for area, bar, and line charts. You can configure the bounds for all functions, except **Percentile**. Logarithmic scales are unsupported.To configure the bounds, use the menus in the editor toolbar. Bar and area charts required 0 in the scale between **Lower bound** and **Upper bound**.
You can display icons with [field formatters](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/find-and-organize/data-views) in data tables.
You can inspect the requests sent by the visualization to Elasticsearch using the Inspector. It can be accessed within the editor or in the dashboard.
For area, line, and bar charts, press Shift, then click the series in the legend. All other series are automatically deselected.
Visualizing saved Discover sessions is unsupported.
Configuring the **Suggestions** is unsupported.
Pagination in a data table is unsupported. To use pagination in data tables, create an [aggregation-based data table](/elastic/docs-builder/docs/3028/explore-analyze/visualize/legacy-editors/aggregation-based#types-of-visualizations).
Specifying the color for a single data point, such as a single bar or line, is unsupported.
In the color palette editor, if you select **Value type: Number** the colors are applied based on the **Primary metric** value.The **Primary metric** refers to the large number displayed in each tile.If you select **Value type: Percent**, the primary metric values are mapped to a range between 0 and 100 percent. The bounds of the range depend on your configuration.The logic is as follows. If there is a Breakdown dimension for multiple visualization tiles:
- When there is a **Maximum dimension**, the range is from zero to the value of your **Maximum dimension**.
- When there is no **Maximum dimension**, the range is from the smallest primary metric values to the greatest primary metric values.
If there is no Breakdown dimension for a single visualization tile:
- When there is a **Maximum dimension**, the range is from zero to the value of your **Maximum dimension**.
- When there is no **Maximum dimension**, **Value type: Percent** cannot be selected because there’s no way to determine a range.