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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

Working with Indexes

Having covered creating various types of pandas indexes, let's now examine several common patterns of use for these indexes. Specifically, we will examine:

  • Creating and using an index with a Series or DataFrame
  • Means of selecting values with an index
  • Moving data to and from the index
  • Reindexing a pandas object

Creating and using an index with a Series or DataFrame

Indexes can either be created explicitly or you can let pandas create them implicitly. Explicit creation takes place when you assign the index using the index parameter of a constructor.

The following code demonstrates by first creating a DatetimeIndex independently.

You can use this index on its own or associate it with a Series or DataFrame...

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