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Pandas Cookbook

You're reading from   Pandas Cookbook Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781784393878
Length 532 pages
Edition 1st Edition
Languages
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Author (1):
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Theodore Petrou Theodore Petrou
Author Profile Icon Theodore Petrou
Theodore Petrou
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Toc

Table of Contents (12) Chapters Close

Preface 1. Pandas Foundations FREE CHAPTER 2. Essential DataFrame Operations 3. Beginning Data Analysis 4. Selecting Subsets of Data 5. Boolean Indexing 6. Index Alignment 7. Grouping for Aggregation, Filtration, and Transformation 8. Restructuring Data into a Tidy Form 9. Combining Pandas Objects 10. Time Series Analysis 11. Visualization with Matplotlib, Pandas, and Seaborn

Using methods that only work with a DatetimeIndex

There are a number of DataFrame/Series methods that only work with a DatetimeIndex. If the index is of any other type, these methods will fail.

Getting ready

In this recipe, we will first use methods to select rows of data by their time component. We will then learn about the powerful DateOffset objects and their aliases.

How to do it...

  1. Read in the crime hdf5 dataset, set the index as REPORTED_DATE, and ensure that we have a DatetimeIndex:
>>> crime = pd.read_hdf('data/crime.h5', 'crime'...
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