Book Image

Pandas 1.x Cookbook - Second Edition

By : Matt Harrison, Theodore Petrou
Book Image

Pandas 1.x Cookbook - Second Edition

By: Matt Harrison, Theodore Petrou

Overview of this book

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 as one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter. This new updated and revised edition provides you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. 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. Many advanced recipes combine several different features across the pandas library to generate results.
Table of Contents (17 chapters)
15
Other Books You May Enjoy
16
Index

Renaming column names

One of the most common operations on a DataFrame is to rename the column names. I like to rename my columns so that they are also valid Python attribute names. This means that they do not start with numbers and are lowercased alphanumerics with underscores. Good column names should also be descriptive, brief, and not clash with existing DataFrame or Series attributes.

In this recipe, the column names are renamed. The motivation for renaming is to make your code easier to understand, and also let your environment assist you. Recall that Jupyter will allow you to complete Series methods if you accessed the Series using dot notation (but will not allow method completion on index access).

How to do it…

  1. Read in the movie dataset, and make the index meaningful by setting it as the movie title:
    >>> movies = pd.read_csv("data/movie.csv")
    
  2. The renamed DataFrame method accepts dictionaries that map the old...