Instructor: Jacob Sanz-Robinson

Outline

This module is designed to introduce students to the Pandas Python library for manipulating data in tables and time series (not to be confused with the bear of the same name).

It aims to build a basic understanding of what happens underneath the hood in Pandas, and arm you with the essential practical knowledge to fearlessly tackle the next CSV file you encounter in the wild.

1. Introduction
2. What is Pandas?
3. (Very) Brief History
4. Why should I care about Pandas?
5. Features & Docs
6. Pandas Objects
   1. The Series Object
   2. The DataFrame Object
   3. The Index Object
7. Pandas Wrangler Essentials
   1. Data I/O
   2. Selection and Indexer
   3. Filtering
   4. Combining DataFrames
   5. Inbuilt Aggregations

Questions you will be able to answer after taking this module

• Which of the following is an immutable Pandas Object?
  1. Index
  2. DataFrame
  3. Series
  4. Array
• What function would you use to combine two Pandas DataFrames if you wanted to align their rows based on common column values?
  1. Append
  2. Concat
  3. Merge
  4. Map

Material

• code
• slides

Resources

• Python Data Science Handbook
• Neurohackademy lecture on Pandas

Pre-recorded lecture video

Extras

• plotting with Pandas

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