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Learning pandas

You're reading from   Learning pandas High performance data manipulation and analysis using Python

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Product type Paperback
Published in Jun 2017
Publisher
ISBN-13 9781787123137
Length 446 pages
Edition 2nd Edition
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Table of Contents (16) Chapters Close

Preface 1. pandas and Data Analysis 2. Up and Running with pandas FREE CHAPTER 3. Representing Univariate Data with the Series 4. Representing Tabular and Multivariate Data with the DataFrame 5. Manipulating DataFrame Structure 6. Indexing Data 7. Categorical Data 8. Numerical and Statistical Methods 9. Accessing Data 10. Tidying Up Your Data 11. Combining, Relating, and Reshaping Data 12. Data Aggregation 13. Time-Series Modelling 14. Visualization 15. Historical Stock Price Analysis

Renaming columns

Columns can be renamed using the appropriately named .rename() method. This method can be passed a dictionary object where the keys represent the labels of the columns that are to be renamed, and the value for each key is the new name.

The following will change the name of the 'Book Value' column to 'BookValue', removing the space and allowing access to that column's data using property notation.

Using .rename() in this manner returns a new data frame with the columns renamed and the data copied from the original. The following verifies that the original was not modified.

To modify the data frame in-place without making a copy you can use the inplace=True parameter.

It is now possible to use the .BookValue property to access the data.

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