Essential Introduction to pandas DataFrame

If you are working with data in Python, chances are Python pandas will make common data tasks easier.

This Python pandas tutorial describes how to use the most frequently used basic data manipulations for the pandas DataFrame. There are many resources for this sort of information, but it is difficult to find one source for what might be considered the most essential functionality in for working with data in the Python environment. Coverage includes:

• Creating DataFrames
• Getting and reading data
• inspecting data
• Filtering and slicing
• Vectorized calculations
• Adding columns and rows
• Data transformation
• Exporting Data

You can download the Jupyter notebook used in the video here.