Looker makes it easy to create graphics and charts based on the results of a query. This page explains how to create visualizations that best show off your data. After reading this page, you’ll be able to create and configure charts.
Looker keeps query details and visualization configuration data together, so when you share a query, recipients get the picture as well as the data.
You can add an eye-catching chart to any query result set on the Explore. This page shows how to create visualizations that best show off your data.
- Create and Run your query.
- Click the Visualization tab to start configuring your visualization options.
- Select the type of visualization that best displays your data. For more options, click … to the right of the displayed visualization options.
- Click Edit to configure the visualization option settings, such as naming and arranging chart axes, choosing the position and type of each data series, or modifying the chart color palette.
You can further customize your visualization by specifying which dimensions and measures you want to be included in the visualization. If your data is missing key values, you can tell Looker to fill in those values on the appropriate part of your visualization.
Choosing a Visualization Type
Once you’ve created and run your query, click the Visualization tab in the Explore to configure visualization options for the query. Use the chart buttons to pick the visualization type that’s right for the data. For more options, click … to the right of the displayed visualization options.
The visualization type you select determines how the data series are represented in your chart. A data series is a set of related data points plotted on a chart. In a column chart a series is represented by columns of the same color, in a line chart, a series is represented by a single line, and so on.
Fine-Tuning Your Visualizations
Learn how to customize your visualizations with the Looker features below.
Customizing Visualizations with Chart Settings
You can customize a visualization to make the data more readable and to add visual styling. Click Edit to see the visualization options, then change the settings to get a result that suits you.
To see the visualization options available for a particular visualization type, go to the bottom of this page to see the documentation page for each visualization type.
The example below shows some of the visualization settings chosen for an area chart with stacked series.
To add POINTS, click Series, choose Filled or Outline under Point Style.
To label totals on the chart, click Values, check Totals Labels.
Including Multiple Visualization Types on a Single Chart
You can also create charts that include more than one visualization type:
- Click the Edit button to show the chart customization options.
- Click the Series tab.
- In the Customizations section, you’ll see an entry for each series in the chart. Click the arrow next to the series you want to change to display its customization options.
- In the Type box, select the type of visualization to use for that series.
Charts with multiple series types always layer line and scatter series in front, then they layer area, column, and bar series.
You can alter the layering order of column, bar, and area series by changing the series’ positions in the data table and click the Run button. The leftmost series will layer on top and the rightmost series will layer on the bottom.
To include multiple Y axes, click Y and then move some of the axes to other places. In the example below, we have Total Net Paid on the left and Transaction Count on the right.
Creating Stacked Charts with Multiple Visualization Types
You can include stacked series in a chart with multiple visualization types. All the series of the same type as the chart overall will be stacked together; series of other types will not stack. For example, the chart below is a column chart, so the columns stack, but the line series do not stack.
To create a stacked chart that uses multiple y-axes, drag any series to a different axis in the Y menu. The stacked series will appear together, but all other series can be moved independently, including individual series within a pivot.
Specifying Fields to Include in the Visualization
All dimensions and measures are automatically added to any visualizations you use. However, sometimes you won’t want to display every dimension or measure in the chart. In the example below, note that the measures Enrollment Count, Client Count, and Paid Count are displayed:
To hide a column from the visualization, select the gear icon at the top right corner of the column, then select Hide from Visualization:
This will hide the column from the visualization. In the example below, the field Paid Count is hidden from the visualization, leaving only Enrollment Count and Client Count in the chart.
You can also enable or disable a charted series by clicking on that series in the visualization’s legend. When disabled, the series color turns grey in the legend and the data disappears in the chart. Click the series again to re-enable it.
Filling in Missing Dates and Values
Some datasets have values, such as dates, that follow a predictable pattern. A user might pull data by a timeframe and find that some dates, weeks, months, or other date types don’t have any corresponding value. By default, the data table and the visualization will display dates returned from the query and skip any dates that are missing. Looker’s "dimension fill" option lets you display the missing dates or other values in the data table and on the corresponding axis of the query’s visualization. This option is found in the dimension’s gear menu in the Data section of an Explore.
For example, this new client data shows only a few dates in which a new client joined:
If you do not dimension fill, Looker connects the data points it has, resulting in a potentially misleading graph.
Turning on dimension fill adds the missing dates and makes the graph more informative:
To use dimension fill simply choose the Fill in Missing Dates or Fill in Missing Values option from the gear menu of the appropriate dimension:
To remove filled dates or values, you can simply click on the gear menu and find the options too.
Dimension fill is available for dimensions with yes/no values, tiered values, and most date types. It can also be applied to any dimension based on a list of values, via the case parameter.
Dimension fill will turn on automatically for queries that run with a single dimension and/or a single pivot, just as long as you haven’t applied filters to any measures.
There are a few cases when you will not be able to dimension fill:
- Dimensions that have a filter applied to them and also have a fixed number of values, such as yes/no, days of the week, days of the month, etc.
- Drilling into a pivoted dimension.
- Dimensions where your Looker developer has disabled auto-fill.
Looker has many different visualizations you can use to make sense of your data. Each type of visualization has different settings you can use to customize its appearance. Use the links below to get information about each visualization and its settings.
Pie and Donut Charts
Text and Tables
Now that you know how to create visualizations and charts, learn how to save a Look.