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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

Slicing time series intelligently

DataFrame selection and slicing was thoroughly covered in Chapter 4, Selecting Subsets of Data. When the DataFrame posses a DatetimeIndex, even more opportunities arise for selection and slicing.

Getting ready

In this recipe, we will use partial date matching to select and slice a DataFrame with a DatetimeIndex.

How to do it...

Read in the Denver crimes dataset from the hdf5 file crimes.h5, and output the column data types and the first few rows. The hdf5 file format allows efficient storage of large scientific data and is completely...

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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.

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