Aggregation

Calculate aggregations such as sums, averages, or unique values.

You can use aggregations in the insight editor to summarize your data — for example, to count how many cities belong to each country or to calculate the average value per region.

To do this, add a column and select an aggregation such as count, sum, or average. All columns without aggregation are automatically used to group the data.

You can combine multiple aggregations in the same table, rename columns for better readability, and even filter based on the result of an aggregation (e.g., "show only countries with more than 450 cities").

It's a quick way to transform detailed datasets into easily readable summaries.

Creating aggregations

Sometimes you don't want to look at every data row. Instead, you want to see a summary — such as:

• The total number of customers

• The average age

• The earliest subscription date

• The number of cities per country

In the insight editor, you can do this with aggregations.

How it works

To summarize your data:

1. Add a column.

2. Click the three dots (•••) next to the column.

3. Select an aggregation function (such as count, average, sum, etc.).

4. Rename the column if desired.

Automatic Grouping

When you apply an aggregation to one column and don't aggregate another, the non-aggregated column becomes the group. For example:

• If you group by Country and count City, you get "How many cities per country".

Examples

Example 1: Counting cities per country.

Let's say you want to see how many cities are listed for each country.

1. Add the Country column → leave it as None

2. Add the City column → Aggregation: Count unique values

3. Rename the column to: Number of Cities

Your result looks like this:

Country	Number of Cities
Germany	540
France	470
Italy	320

In the background, the table is grouped by Country, and the system counts how many unique City values occur per country.

Example 2: Showing average index per city.

Let's say each city has multiple entries with an "Index" value. You want to know the average index per city.

1. Add the City column → leave aggregation as None

2. Add the Index column → Aggregation: Average of values

3. Rename to: Average Index

Your result:

City	Average Index
Berlin	8.3
Hamburg	7.9
Munich	9.1

Example 3: Finding earliest subscription date per region.

You want to see when the first subscription occurred in each region.

1. Add the Region column → leave aggregation as None

2. Add the Subscription Date column → Aggregation: Earliest

3. Rename to: First Subscription

Your result:

Region	First Subscription
North	01/15/2022
South	03/01/2022
West	01/09/2022

Available Aggregation Options

Text columns (e.g., City, Name)

Aggregation	Description
None	Shows each text value as is.
Count existing values	Counts how many rows have something filled in.
Count unique values	Counts how many different (distinct) values exist.
Count missing values	Counts how many rows are empty or null.
Unique values	Lists all unique values in a cell.

Number columns (e.g., Index, Age)

Aggregation	Description
None	Shows each number as is.
Sum of values	Adds all values.
Smallest value	Shows the lowest number.
Largest value	Shows the highest number.
Average of values	Calculates the mean (average).
Count existing values	Counts how many rows have a number.
Count unique values	Counts how many different numbers exist.
Count missing values	Counts how many rows are empty or null.
Unique values	Lists all unique numbers in a cell.

Date columns (e.g., Subscription Date)

Aggregation	Description
None	Shows each date as is.
Earliest	Shows the first (oldest) date.
Latest	Shows the newest date.
Count existing values	Counts how many rows have a date.
Count unique values	Counts how many different dates exist.
Count missing values	Counts how many rows are empty or null.
Unique values	Lists all unique dates in a cell.

Tips for working with aggregations

• You can combine multiple aggregations in a table.

• Rename aggregated columns to make the table more readable.

• Use filters to restrict which rows are counted or averaged.

• You can remove a grouping column later if you only want a total sum.