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You're reading from Learning Pandas Get to grips with pandas - a versatile and high-performance Python library for data manipulation, analysis, and discovery

Product type Paperback

Published in Apr 2015

Publisher Packt

ISBN-13 9781783985128

Length 504 pages

Edition 1st Edition

Languages

Python

Tools

Pandas

Concepts

Data Analysis

Author (1):

Michael Heydt

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Table of Contents (14) Chapters

Preface

1. A Tour of pandas FREE CHAPTER

2. Installing pandas

3. NumPy for pandas

4. The pandas Series Object

5. The pandas DataFrame Object

6. Accessing Data

7. Tidying Up Your Data

8. Combining and Reshaping Data

9. Grouping and Aggregating Data

10. Time-series Data

11. Visualization

12. Applications to Finance

Index

Modifying the structure and content of DataFrame

The structure and content of a DataFrame can be mutated in several ways. Rows and columns can be added and removed, and data within either can be modified to take on new values. Additionally, columns, as well as index labels, can also be renamed. Each of these will be described in the following sections.

Renaming columns

A column can be renamed using the .rename() method of the DataFrame. The Book Value column is inconvenient since it has a space, so we will rename it to BookValue:

In [48]:
   # rename the Book Value column to not have a space
   # this returns a copy with the column renamed
   df = sp500.rename(columns=
                     {'Book Value': 'BookValue'})
   # print first 2 rows
   df[:2]

Out[48]:
                Sector   Price  BookValue
   Symbol                                
   MMM     Industrials  141.14     26.668
   ABT     Health Care   39.60     15.573