Table of Contents
Using the data processing function, you can perform various operations over a column. One operation is the calculation of changes, which allows you to calculate the changes from value to value in a numeric column. To do this, simply define an appropriate data processing operation using the view options of your table.
Putting on the operation
- Open any table and click the three dots in the view options.
- Click Data Processing, and then click Add Data Processing Operation.
- Give the operation a name and select Calculate changes.
- Define table, view, source column and result column.
- Click Save to save the action and execute it later, or Execute to execute the action directly.
On the first successful execution, a small Green hook.
Use case
A concrete use case for this data processing operation could occur, for example, if you collect the number of daily accesses to a website and want to find out how the access numbers have changed in the period between two measurements. For this purpose, you want to calculate the difference between the access numbers in another column.
For the implementation you first need a table in which the different days are collected in a date column and the access numbers to the website in a number column .
Then add a second column of numbers to the table, in which the change in daily access numbers is calculated after the data processing operation is executed. The new, initially empty Visitors compared to last measurement column acts as the result column in the data processing operation, while the Unique Visitors column represents the source column.
To create the data processing operation, follow the steps described above. Next, define the currently opened table and view. Also select the Unique Visitors column as the source column and the Visitors compared to last measurement column as the result column.
Each time the data processing operation is executed, the calculated values are written to the results column. You can execute a saved operation again at any time via the data processing window. Existing values in the result column will be overwritten if necessary.
