Book Image

Pandas 1.x Cookbook - Second Edition

By : Matt Harrison, Theodore Petrou
Book Image

Pandas 1.x Cookbook - Second Edition

By: Matt Harrison, Theodore Petrou

Overview of this book

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 as one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter. This new updated and revised edition provides you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. 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. Many advanced recipes combine several different features across the pandas library to generate results.
Table of Contents (17 chapters)
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Slicing time series intelligently

DataFrame selection and slicing was covered previously. When the DataFrame has a DatetimeIndex, even more opportunities arise for selection and slicing.

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 amounts of data and is different from a CSV text file:
    >>> crime = pd.read_hdf('data/crime.h5', 'crime')
    >>> crime.dtypes
    OFFENSE_TYPE_ID              category
    OFFENSE_CATEGORY_ID          category
    REPORTED_DATE          datetime64[ns]
    GEO_LON                       float64
    GEO_LAT                       float64
    NEIGHBORHOOD_ID              category
    IS_CRIME                        int64
    IS_TRAFFIC                      int64