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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
Other Books You May Enjoy
16
Index

Highlighting the maximum value from each column

The college dataset has many numeric columns describing different metrics about each school. Many people are interested in schools that perform the best for specific metrics.

This recipe discovers the school that has the maximum value for each numeric column and styles the DataFrame to highlight the information.

How to do it…

  1. Read the college dataset with the institution name as the index:
    >>> college = pd.read_csv(
    ...     "data/college.csv", index_col="INSTNM"
    ... )
    >>> college.dtypes
    CITY                   object
    STABBR                 object
    HBCU                  float64
    MENONLY               float64
    WOMENONLY             float64
                           ...
    PCTPELL               float64
    PCTFLOAN              float64
    UG25ABV               float64
    MD_EARN_WNE_P10        object
    GRAD_DEBT_MDN_SUPP     object
    Length: 26, dtype: object
    
  2. All the other columns...

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