um_kod_zm_kat_4.py

# Import libraries
import numpy as np
import pandas as pd

# Display all columns
pd.set_option('display.max_columns', None)

# Import Houseprice data from GitHub
data = pd.read_csv('https://github.com/jurand71/datasets/raw/master/HouseSalePriceCompetition/houseprice.csv')

# Three variables were chosen from categorical variables for OneHotEncoder
usecols = ['Neighborhood','Exterior1st','Exterior2nd']
data = data[usecols]

# How many categories are in selected variables
for col in usecols:
    print(col,': ',len(data[col].unique()))

# Obtain counts for each variable and replace categories by number of counts 
def count_encoding(df, variable):
        count_map = df[variable].value_counts().to_dict()  
        df[variable]=df[variable].map(count_map)

for var in usecols:
    count_encoding(data, var)

data