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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

Re-indexing a Series

Re-indexing in pandas is a process that makes the data in a Series conform to a set of labels. It is used by pandas to perform much of the alignment process and is hence a fundamental operation.

Re-indexing achieves several things:

  • Re-ordering existing data to match a set of labels
  • Inserting NaN markers where no data exists for a label
  • Possibly filling missing data for a label using some type of logic (defaulting to adding NaN values)

Re-indexing can be as simple as simply assigning a new index to the .index property of a Series. The following demonstrates changing the index of a Series in this manner:

The number of elements in the list being assigned to the .index property must match the number of rows or an exception will be thrown. Re-indexing also modified the Series in-place.

Flexibility in creating a new index is provided through use of the .reindex...

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