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Pandas Cookbook

Pandas Cookbook

By : Theodore Petrou
4.3 (32)
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Pandas Cookbook

Pandas Cookbook

4.3 (32)
By: Theodore Petrou

Overview of this book

This book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas 0.20. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands like one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter. Many advanced recipes combine several different features across the pandas 0.20 library to generate results.
Table of Contents (12 chapters)
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Selecting DataFrame rows

The most explicit and preferred way to select DataFrame rows is with the .iloc and .loc indexers. They are capable of selecting rows or columns independently and simultaneously.

Getting ready

This recipe shows you how to select rows from a DataFrame using the .iloc and .loc indexers.

How to do it...

  1. Read in the college dataset, and set the index as the institution name:
>>> college = pd.read_csv('data/college.csv', index_col='INSTNM')
>>> college.head()
  1. Pass an integer to the .iloc indexer to select an entire...
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Pandas Cookbook
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