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Pandas 1.x Cookbook - Second Edition

You're reading from  Pandas 1.x Cookbook - Second Edition

Product type Book
Published in Feb 2020
Publisher Packt
ISBN-13 9781839213106
Pages 626 pages
Edition 2nd Edition
Languages
Authors (2):
Matt Harrison Matt Harrison
Profile icon Matt Harrison
Theodore Petrou Theodore Petrou
Profile icon Theodore Petrou
View More author details

Table of Contents (17) Chapters

Preface Pandas Foundations Essential DataFrame Operations Creating and Persisting DataFrames Beginning Data Analysis Exploratory Data Analysis Selecting Subsets of Data Filtering Rows Index Alignment Grouping for Aggregation, Filtration, and Transformation Restructuring Data into a Tidy Form Combining Pandas Objects Time Series Analysis Visualization with Matplotlib, Pandas, and Seaborn Debugging and Testing Pandas Other Books You May Enjoy
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...
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