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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 FREE CHAPTER 2. Up and Running with pandas 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

Removing rows using Boolean selection

Boolean selection can also be used to remove rows from a DataFrame. The result of a Boolean selection will return a copy of rows where the expression is True. To drop rows, simply construct an expression that returns False for the rows that are to be dropped and then apply the expression to the data frame.

The following demonstrates dropping rows where Price is greater than 300. First, construct the expression.

From this result, we now know that there are 10 rows where the price is greater than 300. To get a data frame with those rows removed, select the complement of the selection.

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