house_type_sidewalks.py

#Import statements to get required modules
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.pyplot import pie, axis, show
%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)

#Summing up the houses
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['Side_Walk'] = test_frame['Side_Walk'].astype(int)
sums = test_frame.Side_Walk.groupby(test_frame.House_Type).sum()

#Plotting the data
sns.set_style("whitegrid")
sns.set_context("poster")
ax = sns.barplot(x=sums.index, y=sums, data=test_frame)
ax.set(xlabel='House Type', ylabel='Number of houses with Side Walks')
plt.title('No of houses of various classes having Sidewalks')