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Pandas 1.x Cookbook

Pandas 1.x Cookbook

By : Matthew Harrison, Theodore Petrou
4.5 (28)
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Pandas 1.x Cookbook

Pandas 1.x Cookbook

4.5 (28)
By: Matthew 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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15
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16
Index

Tidying when variables are stored in column names and values

One particularly difficult form of messy data to diagnose appears whenever variables are stored both horizontally across the column names and vertically down column values. This type of dataset usually is not found in a database, but from a summarized report that someone else has already generated.

How to do it…

In this recipe, data is reshaped into tidy data with the .melt and .pivot_table methods.

  1. Read in the sensors dataset:
    >>> sensors = pd.read_csv('data/sensors.csv')
    >>> sensors
      Group     Property  2012  2013  2014  2015  2016
    0     A     Pressure   928   873   814   973   870
    1     A  Temperature  1026  1038  1009  1036  1042
    2     A         Flow   819   806   861   882   856
    3     B     Pressure   817   877   914   806   942
    4     B  Temperature  1008  1041  1009  1002  1013
    5     B         Flow   887   899   837   824   873
    
  2. The only variable...

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