Which of the following interactive tables uses calculations to consolidate and summarize information?

Pivot tables let you narrow down a large data set or analyze relationships between data points. Pivot tables reorganize your dimensions and metrics to help you quickly summarize your data and see relationships that might otherwise be hard to spot.

In this article:

• Pivot tables in Data Studio
• Data properties
• Style properties
• Limits of pivot tables
• Related resources

Pivot tables in Data Studio

Pivot tables in Data Studio take the rows in a standard table and pivot them so they become columns. This lets you group and summarize the data in ways a standard table can't provide.

Example:

The following is a standard table listing the Revenue Per User metric by calendar quarter and year:

Example table showing revenue per user, by country, quarter, and year.

While this table is useful for showing which country received the most revenue per user and in which quarter, it isn't useful for summarizing this data in a meaningful way.

A pivot table, however, quickly shows the relationship of this data:

Example pivot table showing revenue per user, by country, quarter, and year

This table easily summarizes the data from the previous example. You can also quickly spot outliers or anomalies in your data. Notice that several countries had no revenue in Q4, for example.

Pivot tables in Data Studio support adding multiple row and column dimensions. The example below adds the Gender dimension to the rows. This further breaks down the data, giving you even more insight into your data:

Example pivot table showing Gender as breakdown dimension.

Show totals

Pivot tables support totals and subtotals for both rows and columns:

Example pivot table showing totals and subtotals.

Expand-collapse

Expand-collapse lets report viewers show or hide different levels of information in the pivot table by clicking + and – in the column header. Viewers can then explore the data at the level of detail that interests them most. Expand-collapse also provides a way for a single pivot table to show both summary and detailed information, reducing the number of charts needed in your reports.

Example pivot table showing expand-collapse with a geographic hierarchy.

Configure the chart

Select the chart, then on the right, use the properties panel to configure the chart options.

Setup properties

The options in a chart's setup panel determine how the data is organized and displayed.

Data source

A data source provides the connection between the component and the underlying data set. 

• To change the chart's data source, click the current data source name.
• To view or edit the data source, click . (You must have at least view permission to see this icon.)
• Click +BLEND DATA to see data from multiple data sources in the same chart. Learn more about data blending.

Dimension 

Dimensions are data categories. Dimension values (the data contained by the dimension) are names, descriptions or other characteristics of a category.

Row Dimension

The row dimensions provide the breakdown of rows in the pivot table. Reorder the dimensions listed to change the order of the rows in your table.

Expand-collapse

Turn on expand-collapse to treat the row dimensions as an expandable hierarchy.

The order in which you list the dimensions within the hierarchy matters. As a rule of thumb, you should define hierarchies to always go from the most general to the most specific. For example, defining a geographic hierarchy as Country > City > Region could produce undesirable results, because you're going from a general level to a more detailed level, then back to a more general level.

When you add a Date or Date & TIme type field or a Geo type field as the row dimension, then turn on expand-collapse, Data Studio automatically populates the dimension hierarchy with related fields.

Default expand level

Set the level of detail to show by default. For example, in a geographic hierarchy consisting of Continent > Sub Continent > Country, setting the default expand level to Country would show Continent and Sub Continent details.

Column Dimension

The column dimensions provide the columns in the pivot table. Reorder the dimensions listed to change the order of the columns in your table.

Date range dimension

This option appears if your data source has a valid date dimension. For Google Ads and Analytics data sources, this option is automatically set to the Date dimension.

The Date range dimension is used as the basis for limiting the date range of the chart. For example, this is the dimension used if you set a date range property for the chart, or if a viewer of the report uses a date range control to limit the time frame.

Metric

Metrics measure the things contained in dimensions and provide the numeric scale and data series for the chart.

Metrics are aggregations that come from the underlying data set, or that are the result of implicitly or explicitly applying an aggregation function, such as COUNT(), SUM(), or AVG(). The metric itself has no defined set of values, so you can’t group by it, as you can with a dimension.

Learn more about aggregation.

Totals

Display totals for each row and column. If you have only 1 dimension in a row or column, the option is to display a grand total. If you have 2 or more dimensions, the options include subtotals and grand totals.

Sorting

The sorting options let you control the order of the data displayed in the pivot table. In addition, you can limit the number of rows and columns displayed.

Default date range

The default date range property lets you set a timeframe for an individual chart.

Default date range options

Learn more about working with dates and time. 

Filter

Filters restrict the data that is displayed in the component by including or excluding the values you specify. Learn more about the filter property.

Filter options

Google Analytics segment

This option appears for charts based on a Universal Analytics data source.

A segment is a subset of your Analytics data. You can apply segments to your Data Studio charts to help ensure that your Data Studio and Google Analytics reports show the same data. Learn more about Analytics segments in Data Studio.

Interactions

When interactions are enabled on a chart, that chart acts like a filter control. You can filter the report by clicking or brushing your mouse across the chart. Learn more about chart interaction filters.

Style properties

A chart's style properties control the overall presentation and appearance of the chart.

Table Header

These options control the appearance of the data labels.

Table Colors

These options control the colors of the table borders and cells.

Table Labels

These options control the appearance of the table data.

Missing data

This option controls how to display missing values. For example, when data is missing from the table, you can choose to show blanks, hyphens, or the words "no data."

Metric

This section controls the appearance of the metrics.

Background and border

These options control the appearance of the chart background container.

Limits of pivot tables

• Pivot tables can process up to 50,000 rows of data, however, depending on the data set and dimensions and metrics involved in the table, performance may degrade. You can apply a filter to the pivot table to reduce the amount of data being processed.
• You may have up to 5 pivot tables per page in a report.
• The number of row dimensions available depends on the type of data you're connecting to:
  • Fixed-schema data sources, such as Google Ads and Google Analytics, can have up to 5 row dimensions.
  • Flexible-schema data sources, such as Google Sheets and BigQuery, can have up to 10 row dimensions.
• Pivot tables can have up to 2 column dimensions.
• Pivot tables can have up to 10 metrics.
• Pivot tables do not paginate, as do standard tables.
• You can't apply metric filters to pivot tables; doing so displays an error message.

• Table reference
• Work with dates and time
• Filter property

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