Pivoting/Group By

This documentation will teach you how to create pivot tables in Mito.

What is a pivot table?
A pivot table is a method of aggregating a dataframe within one or more discrete categories you create. This aggregation might include sums, averages, or other statistics, which the pivot table groups together using a chosen aggregation function applied to the grouped values.
If you're used to doing "group bys" in Pandas, or using Excel Pivot Tables, then you're looking for Pivoting in Mito!
Creating a pivot table
Click on the Pivot icon in the Mito toolbar.
Add a column to the Rows section to construct a key to group the dataframe by.
Optionally, to stratify the groups into individual cells, add a column to the Columns section.
Add a column to the the Values section to aggregate data within the buckets defined by Rows and Columns above.
Optionally, switch the aggregation method of the column in the Values section.
Optionally, add and configure Filters on the pivot table. Notably, these filters are applied to the source dataset before it is pivoted. 
Group Dates within in Pivot Tables
If you're aggregating based on a datetime column (aka: you have a datetime column in either the Rows or Columns section), you can select how to group the date. 
By default, Mito will group dates by exact time. This means that two rows will be put in the same bucket within the pivot table if the datetime column matches to the exact second. 
However, if you wish to aggregate based on the year, then you can change the group date by to year. This will ignore months, days, minutes, and seconds, and combine all rows in the same year into the same bucket. Create a pivot table to explore all the ways to group dates.
If the group date by option does not appear after adding a column to the Rows or Columns section of a pivot table, ensure that you have changed the dtype of that column to a datetime first.

Graph Export

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Filter out Rows

Last modified 2mo ago