Jan 5
Make Pivot Tables in Python with Mito
Pivot tables are an essential way to understand your data. Grouping data allows you to see patters and retrieve insights that you would otherwise miss by looking at the raw dataset. I see pivot tables as the most basic form of data visualization. While there are no colors, animations, or graphics, pivot tables can paint an extremely clear picture of your data and allow for quick, shareable insights. I often find that a pivot table will communicate my analysis more effectively than a chart.
In Excel, pivot tables are quite easy to configure — all you have to do is select your rows, columns, and values in point and click menu.
Python pivot tables are harder. The pivot_table function has 11 potential arguments you can fill out.
When making pivot tabes in Python, a lot of your time can be spent going to Google, Stack Overflow or other tutorials to find the right syntax and how to apply it. This is obviously time consuming and takes you away from your analysis, making it harder to stay concentrated on the task.
With Mito, you can create complete pivot tables inside Python without any coding required. Mito is a spreadsheet GUI for Python, meaning each edit you make in Mito will generate the equivalent Python automatically.
You can install Mito for free with the instructions found here. Mito pivot tables have the feel of an Excel pivot table, but can handle the data sizes you are accustomed to in Python. Also, each pivot table you make in Mito, will generate the equivalent Python in the cell below!
Within Mito, you can select the pivot table button and a menu will open to configure your pivot table. Here, you can select the rows, columns, values and aggregation types that you want to use to configure your data.
In the code cell below, the equivalent Python for the action will be auto-generated. This code is auto-documented as well!
Here is a video I made that shows Mito pivot tables in more detail. Check it out if you are interested!
