Visualizations

Azure Databricks notebooks have built-in support for charts and visualizations. The visualizations described in this section are available when you use the display command to view a data table result as a pandas or Apache Spark DataFrame in a notebook cell.

For information about legacy Databricks visualizations, see Legacy visualizations.

Create a new visualization

To create a visualization from a cell result, the notebook cell must use a display command to show the result. Click + and select visualization from menu. The visualization editor appears.

New visualization menu

  1. In the Visualization Type drop-down, choose a type.

    Visualization editor

  2. Select the data to appear in the visualization. The fields available depend on the selected type.

  3. Click Save.

Visualization tools

If you hover over the top right of a chart in the visualization editor, a Plotly toolbar appears where you can perform operations such as select, zoom, and pan.

Notebook visualization editor toolbar

If you hover over the top right of a chart in a notebook, a subset of tools appears:

Notebook chart toolbar

Visualization types

Create a new data profile

Note

Available in Databricks Runtime 9.1 LTS and above.

Data profiles display summary statistics of an Apache Spark DataFrame, a pandas DataFrame, or a SQL table in tabular and graphic format. To create a data profile from a results cell, click + and select data profile from menu.

Data profile new visualization menu

Azure Databricks calculates and displays the summary statistics.

Data Profile

  • Numeric and categorical features are shown in separate tables.
  • At the top of the tab, you can sort or search for features.
  • At the top of the chart column, you can choose to display a histogram (Standard) or quantiles.
  • Check expand to enlarge the charts.
  • Check log to display the charts on a log scale.
  • You can hover your cursor over the charts for more detailed information, such as the boundaries of a histogram column and the number of rows in it, or the quantile value.

You can also generate data profiles programmatically; see summarize command (dbutils.data.summarize).

Work with visualizations and data profiles

Note

Data profiles are available in Databricks Runtime 9.1 LTS and above.

In this topic:

Rename, duplicate, or remove a visualization or data profile

To rename, duplicate, or remove a visualization or data profile, click the three vertical dots at the right of the tab name.

Notebook visualization drop down menu

You can also change the name by clicking directly on it and editing the name in place.

Edit a visualization

Click Edit visualization button beneath the visualization to open the visualization editor. When you have finished making changes, click Save.

Edit colors

You can customize a visualization’s colors when you create the visualization or by editing it.

  1. Create or edit a visualization.
  2. Click Colors.
  3. To modify a color, click the square and select the new color by doing one of the following:
    • Click it in the color selector.
    • Enter a hex value.
  4. Click anywhere outside the color selector to close it and save changes.

Temporarily hide or show a series

To hide a series in a visualization, click the series in the legend. To show the series again, click it again in the legend.

To show only a single series, double-click the series in the legend. To show other series, click each one.

Download a visualization

To download a visualization in .png format, click the camera icon camera iconin the notebook cell or in the visualization editor.

  • In a notebook cell, the camera icon appears at the upper right when you move the cursor over the cell.

    camera in notebook cell

  • In the visualization editor, the camera icon appears when you move the cursor over the chart. See Visualization tools.

    camera in visualization editor

Add a visualization or data profile to a dashboard

  1. Click the three vertical dots at the right of the tab name.

    Add to dashboard

  2. Select Add to dashboard. A list of available dashboard views appears, along with a menu option Add to new dashboard.

  3. Select a dashboard or select Add to new dashboard. The dashboard appears, including the newly added visualization or data profile.