This documentation will teach you how to create pivot tables in Mito.
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!
- Click on the
Pivoticon in the Mito toolbar.
- Add a column to the
Rowssection to construct a key to group the dataframe by.
- Optionally, to stratify the groups into individual cells, add a column to the
- Add a column to the the
Valuessection to aggregate data within the buckets defined by
- Optionally, switch the aggregation method of the column in the
- Optionally, add and configure
Filterson the pivot table. Notably, these filters are applied to the source dataset before it is pivoted.
If you're aggregating based on a
datetimecolumn (aka: you have a
datetimecolumn in either the
Columnssection), 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
datetimecolumn matches to the exact second.
However, if you wish to aggregate based on the
year, then you can change the
group date byto
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.
group date byoption 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