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This article is about Looker Studio. For Looker documentation, visit https://cloud.google.com/looker/docs/intro.

Add comparison metrics and running totals

Compare row data to total and running values in your charts.

You can add metrics that compare each row of your data to the total value of a column. You can also apply running calculations to the data in your charts.

Add comparison metrics to a chart

  1. Edit your report.
  2. Select a chart.
  3. In the Properties panel, select the SETUP tab.

  4. Choose a metric and click its edit pencil .
  5. Click the Comparison calculation menu, and select the desired comparison.
  6. To display the metric's native value, change the Comparison calculation selection to None.

The metric configuration options dialog, where you can edit the field name, change the aggregation and field type, and apply a comparison or running calculation.

Compare to total

You can compare each row of data to the overall total for that field:

  • Percent of total shows the current row's value divided by the column total.
  • Difference from total shows the column total minus the current row's value.
  • Percent difference from total shows the column total minus the current row's value divided by the column total.

For each of these total comparisons, you can also select Ignore canvas filters in total to compute the total value without applying viewer-applied filters, such as controls. Total rows still include filter properties.

Example

The following table shows the results of applying different "compare to total" options to the Order value field.This lets you evaluate each order's contribution to overall sales.

Item Quantity sold Order value Percent of total Difference from total Percent difference from total
Pretty Bird Bird Seed

20

31.96 12.79% -217.85 -87.21%
Healthy Dog Dog Food 16 79.96 32.01% -169.85 -67.99%
Playful Puppy Toy 11 17.97 7.19% -231.84 -92.81%
Parrot Perch 8 74.97 30.01% -174.84 -69.99%
Happy Cat Catnip 4 14.97 5.99% -234.84 -94.01%
Hungry Kitty Cat Food 3 29.98 12% -219.83 88%
Grand total 62 249.81 100% 0 0%

Compare to max

You can compare each row of data to the maximum value for that field:

  • Percent of max shows the current row's value divided by the maximum value.
  • Difference from max shows the current row's value minus the maximum value.
  • Percent difference from max shows the current row's value minus the maximum value divided by the maximum value.

Example

The following table shows the results of applying different "compare to max" options to the Order value field. This lets you see how each order compares to the maximum order.

Item Quantity sold Order value Percent of max Difference from max Percent difference from max
Pretty Bird Bird Seed

20

31.96 39.97% -48 -60.03%
Healthy Dog Dog Food 16 79.96 100% 0 0%
Playful Puppy Toy 11 17.97 22.47% -61.99 -77.53%
Parrot Perch 8 74.97 93.76% -4.99 -6.24%
Happy Cat Catnip 4 14.97 18.72% -64.99 -81.28%
Hungry Kitty Cat Food 3 29.98 37.49% -49.98 -62.51%

Relative comparison

When your chart includes a comparison date range, you can apply the comparison function to either the base data or to the corresponding comparison date range.

For example, consider a time series chart that compares the current 28 days to the previous 28 days. The maximum value of Sessions for the current period was 1,947 on June 26. The maximum value of Sessions for the previous period was 1,571 on June 4.

Time series chart tooltip making two data comparisons: the first between June 26 and May 29, and the second between July 2 and June 4.

If you apply the Percent of max function relative to base data, then every data point for the previous period will be divided by the maximum value of the current period (1,947). For the data point on June 4, the Percent of max relative to base data would be: 1571/1947 = 80.69%.

Time series chart tooltip with percent of max function applied relative to the base data displaying the percentage of max value for June 4.

If you instead apply the Percent of max function relative to corresponding data, then every data point for the previous period will be divided by the maximum value of the previous period (1,571). For the data point on June 4, the Percent of max relative to corresponding data would be: 1571/1571 = 100%.

Time series chart tooltip with percent of max function applied relative to corresponding data displaying the percentage of max value for June 4.

Apply running calculations

Running calculations compute summary results across a collection of values. Running calculations return a value for each row of input, expressing that row's relation to the collection as a whole.

The following example shows the application of two running calculations to the Users metric:

  • Running sum
  • Running delta

Example

Date Source Users Running sum of users Running delta of users
May 7, 2018 google 1,400 1,400 1,400
May 8, 2018 google 1,856 3,256 456
May 9, 2018 google 1,748 5,004 -108
May 10, 2018 google 2,046 7,050 298
May 11, 2018 google 1,497 8,547 -549
May 12, 2018 google 1,094 9,641 -403

See a demonstration report here.

Looker Studio supports the following running calculations:

  • Running sum
  • Running average
  • Running min
  • Running max
  • Running count
  • Running delta
  • Running percentage delta

To apply a running calculation

  1. Edit your report.
  2. Select a chart.
  3. In the Properties panel, select the SETUP tab.

  4. Add a metric to chart, and then click its edit pencil .
  5. Click the Running calculation menu, and select the desired function.
  6. To remove a running calculation, change the Running calculation option to None.
To display the original metric and the metric comparison or running calculation in the same chart, add a second instance of the original metric by dragging it from the Available Fields panel. (You can't add a duplicate field using the metric or dimension picker.)

Differences between running calculations and calculated fields

Calculated fields work on the data in your charts on a row-by-row basis. Running calculations work across rows, making it easy to show complex data relationships without having to code custom SQL queries in your dataset. Such queries would be difficult if not impossible to replicate in a calculated field in your data source.

However, unlike with calculated fields, you can't edit the formulas of running calculations.

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