sidewalks_class.py

#Import statements to get required modules
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
import math

#Loading the dataset into a dataframe
df=pd.read_csv('./Housing_Dataset.csv',encoding ='latin1')
dic={'House_Type':df['house_types'],'Side_Walk':df['sidewalk_ok']}
test_frame=pd.DataFrame(dic)

# Aggregating the results
dic1={'Residence':df['residential_yes']}
test_frame
test_frame=test_frame.dropna(axis=0, how='any')
mymap = {'yes':1, 'no':0,'Not sure, mixed':0}
test_frame=test_frame.dropna(axis=0, how='any')
test_frame = test_frame.reset_index(drop=True)
test_frame=test_frame.applymap(lambda s: mymap.get(s) if s in mymap else s)
test_frame['Residence']=pd.DataFrame(dic1)

# Plotting the results
sns.set_context("poster")
sns.factorplot(x="House_Type", y="Side_Walk", hue="Residence", data=test_frame, kind="bar",size=4, aspect=4)
plt.xlabel('House_Type')
plt.ylabel('Fraction of houses having SideWalk')
plt.title('Fraction of residential and non residential houses having SideWalk per class')