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Pandas 1.x Cookbook

You're reading from   Pandas 1.x Cookbook Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781839213106
Length 626 pages
Edition 2nd Edition
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Authors (2):
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Theodore Petrou Theodore Petrou
Author Profile Icon Theodore Petrou
Theodore Petrou
Matthew Harrison Matthew Harrison
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Matthew Harrison
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Toc

Table of Contents (17) Chapters Close

Preface 1. Pandas Foundations 2. Essential DataFrame Operations FREE CHAPTER 3. Creating and Persisting DataFrames 4. Beginning Data Analysis 5. Exploratory Data Analysis 6. Selecting Subsets of Data 7. Filtering Rows 8. Index Alignment 9. Grouping for Aggregation, Filtration, and Transformation 10. Restructuring Data into a Tidy Form 11. Combining Pandas Objects 12. Time Series Analysis 13. Visualization with Matplotlib, Pandas, and Seaborn 14. Debugging and Testing Pandas 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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