Aggregation is the process of reducing and summarizing tabular data. For example, consider the list of numbers below:
100, 200, 300, 400, 500
Using this example, you can state the following facts that illustrate the concept of aggregation:
| Fact | Aggregation |
|---|---|
| There are 5 numbers. | Count |
| The smallest number is 100 | Minimum |
| The largest number is 500 | Maximum |
| The average of the numbers is 300 | Average |
| The sum of the numbers is 1500 | Sum |
There are other ways you can aggregate data, including calculating the median, count distinct, quartiles, percentiles, etc.
Dimensions and aggregation
The example above is based on a single set of numbers, but that’s almost never what you see in the real world. In the real world, your data is typically organized into dimensions and metrics. Dimensions provide a way to categorize and group your data, while metrics measure that data.
In Looker Studio, aggregation always takes place in the context of a set of dimensions. That set of dimensions can be:
- Every dimension, which lets you see the raw data.
- A subset of your dimensions, which lets you see data broken down (grouped) by the dimensions you select.
- The empty set, which lets you see a summary of the entire data set.
For example, here are the same five numbers presented as daily stock prices. Date and Ticker are dimensions, Price is a metric.
| Date | Ticker | Price |
| January 1 | GOOG | 100 |
| January 1 | AAPL | 200 |
| January 2 | GOOG | 300 |
| January 2 | AAPL | 400 |
| January 3 | GOOG | 500 |
You can now use the dimensions to group the data in different ways. For example:
By Ticker
| Ticker | Price |
| GOOG | ? |
| AAPL | ? |
By Date
| Date | Price |
| January 1 | ? |
| January 2 | ? |
| January 3 | ? |
In the examples above, the metric values depend on what you want to know about the data. For example, to calculate the average price for each company, apply the Average aggregation in conjunction with the Ticker dimension:
| Ticker | Average of Price |
| GOOG | (100 + 300 + 500) / 3 = 300 |
| AAPL | (200 + 400) / 2 = 300 |
To see how many companies had stock information on a given day, you would use the Date dimension and the Count aggregation:
| Date | Count of Price |
| January 1 | 2 |
| January 2 | 2 |
| January 3 | 1 |
Now, consider what happens when you use both the Date and Ticker dimensions in the stock table:
| Date | Ticker | AVG(Price) | SUM(Price) |
| January 1 | GOOG | 100 | 100 |
| January 1 | AAPL | 200 | 200 |
| January 2 | GOOG | 300 | 300 |
| January 2 | AAPL | 400 | 400 |
| January 3 | GOOG | 500 | 500 |
When you create a group that includes all the available dimensions, the result is identical to the original data. This is still an aggregation, just not an interesting one, since every aggregation gives the same result. In Looker Studio, if you make a table and show every dimension, you’re still able to set the aggregation type but it won’t do anything.
Aggregation in Looker Studio
There are several ways to apply an aggregation method to your data in Looker Studio:
In the data source. A field's default aggregation determines how that metric is displayed in charts. See below for the available default aggregations.
In a chart. Report editors can override the default aggregation and apply a different one to the metric on a chart by chart basis. Learn how to add and edit data in charts.
In a calculated field. You can use specific aggregation functions within a calculated field formula to produce aggregated metrics. See the list of functions.
Default aggregation
You can apply the following default aggregations to fields in data sources.
| Aggregation Method | Abbreviation | Description |
|---|---|---|
| Sum | SUM | The field values are added together. |
| Average | AVG | The field values are averaged. |
| Count | CT | Each field value is counted. |
| Count Distinct | CTD | Only unique field values are counted. |
| Min | MIN | The field displays the minimum value. |
| Max | MAX | The field displays the maximum value. |
| Auto | AUT | You can't apply this method directly. The aggregation method is supplied by the underlying data set, or as the result of a calculated field.
You can't change the Auto aggregation method. |
| None |
No aggregation is applied. The field is treated as a dimension, even if it contains numeric data. Note: This method only appears in the data source. The default aggregation for metrics in reports is Sum.
|
Change the aggregation method
To change the field's aggregation method, edit the data source, then use the Default aggregation drop-down menu..
Auto aggregation
Some data sources, such as Google Analytics and Google Ads, show Auto as the only available aggregation type for metrics. These data sets are already aggregated, reducing a potentially massive list of numbers to single values. The aggregations used can be simple, like sum or count, or more complex, like percentile. You can't change Auto aggregated metrics to a different aggregation type, since doing so would require Looker Studio to have access to the raw, unaggregated data.
You'll also see Auto aggregation applied to calculated fields based on other data sources, such as Sheets. In this case, the aggregation is a direct result of using an aggregation function in the formula, such as AVG(Price). Again, you can't change the Auto aggregation here, because that would conflict with the output of the AVG function.