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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

Adding new columns with [] and .insert()

New columns can be added to a data frame using the [] operator. Let's add a new column named RoundedPrice which will represent the rounding of values in the Price column.

The way that pandas performs this is by first selecting the Price column's data from sp500 and then all of the values in that Series are rounded. Then pandas aligns this new Series with the copy DataFrame and adds it as a new column named RoundedPrice. The new column is added to the end of the columns index.

The .insert() method can be used to add a new column at a specific location. The following inserts the RoundedPrice column between Sector and Price:

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