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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

Removing rows using a slice

Slicing can be used to remove records from a data frame. It is a process similar to Boolean selection where we select out all of the rows except for the ones you want removed.

Suppose we want to remove all but the first three records from sp500. The slice to perform this task is [:3] which returns the first three rows.

Remember, that since this is a slice, the result is a view into the original data frame. The rows have not been removed from the sp500 data, and changes to these three rows will change the data in sp500. The proper action to prevent this is to make a copy of the slice which results in a new data frame with the data for the specified rows copied.

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