Book Image

Pandas Cookbook

By : Theodore Petrou
Book Image

Pandas Cookbook

By: Theodore Petrou

Overview of this book

This book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas 0.20. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands like one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter. Many advanced recipes combine several different features across the pandas 0.20 library to generate results.
Table of Contents (12 chapters)

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...

  1. 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...