stats_by_group.py

# We'll group by a given column and calculate statistics for
# each group
#
# Reference:
# https://datascienceparichay.com/article/pandas-groupby-median/

import pandas as pd

if __name__ == "__main__":
    df = pd.DataFrame({
        'Address': ['123 Main Street', '456 Centerline Road', '323 Arden Way', '5000 Smith Lane', '200 Darling Way', '1920 Cesna Blvd'],
        'ZipCode': ['95431', '95630', '95630', '95431', '95630', '95431'],
        'SalePrice': [425000, 376000, 571432, 498321, 387499, 430060]
    })

    print('\nHere is the data frame we are using')
    print(df)

    print('\nA data frame can be grouped by one or more columns')
    df_groups = df.groupby('ZipCode')

    print('Then aggregate functions can be run on a column for each group')
    median_by_zip = df_groups ['SalePrice'].median()
    average_by_zip = df_groups ['SalePrice'].mean()
    min_by_zip = df_groups ['SalePrice'].min()
    max_by_zip = df_groups ['SalePrice'].max()

    print('\nHere is the median of each zip code')
    print(median_by_zip)

    print('\nHere is the average of each zip code')
    print(average_by_zip)

    print('\nHere is the min of each zip code')
    print(min_by_zip)

    print('\nHere is the max of each zip code')
    print(max_by_zip)