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Pandas Cookbook

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

Product type Paperback

Published in Oct 2017

Publisher Packt

ISBN-13 9781784393878

Length 532 pages

Edition 1st Edition

Languages

Python

Tools

Pandas

Concepts

Data Analysis

Author (1):

Theodore Petrou

View More author details

Table of Contents (12) Chapters

Preface

1. Pandas Foundations

2. Essential DataFrame Operations FREE CHAPTER

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

Grouping with anonymous functions with a DatetimeIndex

Using DataFrames with a DatetimeIndex opens the door to many new and different operations as seen with several recipes in this chapter.

Getting ready

In this recipe, we will show the versatility of using the groupby method for DataFrames that have a DatetimeIndex.

How to do it...

Read in the Denver crime hdf5 file, place the REPORTED_DATE column in the index, and sort it:

>>> crime_sort = pd.read_hdf('data/crime.h5', 'crime') \
                   .set_index('REPORTED_DATE') ...

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Authors (1)

Theodore Petrou

Theodore Petrou

Theodore Petrou is the founder of Dunder Data, a training company dedicated to helping teach the Python data science ecosystem effectively to individuals and corporations. Read his tutorials and attempt his data science challenges at the Dunder Data website.

See other products by Theodore Petrou

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