How to rank a Pandas DataFrame?

This recipe helps you rank a Pandas DataFrame

This python source code does the following : 1. Creates and converts data dictionary into pandas dataframe 2. Creates new columns in the dataframe 3. Ranks dataframe in ascending and descending order

In [1]:

## How to rank a Pandas DataFrame
def Kickstarter_Example_100():
    print()
    print(format('How to rank a Pandas DataFrame','*^82'))

    import warnings
    warnings.filterwarnings("ignore")

    # load libraries
    import pandas as pd

    # Create dataframe
    data = {'name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'],
            'year': [2012, 2012, 2013, 2014, 2014],
            'reports': [4, 24, 31, 2, 3],
            'coverage': [25, 94, 57, 62, 70]}

    df = pd.DataFrame(data, index = ['Cochice', 'Pima', 'Santa Cruz', 'Maricopa', 'Yuma'])
    print(); print(df)

    # Create a new column that is the rank of the value of coverage in ascending order
    df['coverageRanked'] = df['coverage'].rank(ascending=True)
    print(); print(df)

    # Create a new column that is the rank of the value of coverage in descending order
    df['coverageRanked'] = df['coverage'].rank(ascending=False)
    print(); print(df)

Kickstarter_Example_100()

**************************How to rank a Pandas DataFrame**************************

             name  year  reports  coverage
Cochice     Jason  2012        4        25
Pima        Molly  2012       24        94
Santa Cruz   Tina  2013       31        57
Maricopa     Jake  2014        2        62
Yuma          Amy  2014        3        70

             name  year  reports  coverage  coverageRanked
Cochice     Jason  2012        4        25             1.0
Pima        Molly  2012       24        94             5.0
Santa Cruz   Tina  2013       31        57             2.0
Maricopa     Jake  2014        2        62             3.0
Yuma          Amy  2014        3        70             4.0

             name  year  reports  coverage  coverageRanked
Cochice     Jason  2012        4        25             5.0
Pima        Molly  2012       24        94             1.0
Santa Cruz   Tina  2013       31        57             4.0
Maricopa     Jake  2014        2        62             3.0
Yuma          Amy  2014        3        70             2.0

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