Covid19_Web_Scraper.py

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import requests 
from bs4 import BeautifulSoup
from prettytable import PrettyTable

# offical ministry of health website
url = 'https://www.mohfw.gov.in/' 

# make a GET request to fetch the raw HTML content
web_content = requests.get(url).content

# parse the html content
soup = BeautifulSoup(web_content, "html.parser")

# remove any newlines and extra spaces from left and right
extract_contents = lambda row: [x.text.replace('\n', '') for x in row] 

stats = [] # initialize stats
all_rows = soup.find_all('tr') # find all table rows 

for row in all_rows: 
    stat = extract_contents(row.find_all('td')) # find all data cells  
    # notice that the data that we require is now a list of length 5
    if len(stat) == 5: 
        stats.append(stat)


# now convert the data into a pandas dataframe for further processing
new_cols = ["Sr.No", "States/UT","Confirmed","Recovered","Deceased"]
state_data = pd.DataFrame(data = stats, columns = new_cols)

# converting the 'string' data to 'int'
state_data['Confirmed'] = state_data['Confirmed'].map(int)
state_data['Recovered'] = state_data['Recovered'].map(int)
state_data['Deceased']  = state_data['Deceased'].map(int)

# pretty table representation
table = PrettyTable()
table.field_names = (new_cols)
for i in stats:
    table.add_row(i)
table.add_row(["","Total", 
               sum(state_data['Confirmed']), 
               sum(state_data['Recovered']), 
               sum(state_data['Deceased'])])
print(table)


# barplot to show total confirmed cases Statewise 
sns.set_style("ticks")
plt.figure(figsize = (15,10))
plt.barh(state_data["States/UT"], state_data["Confirmed"].map(int),
         align = 'center', color = 'lightblue', edgecolor = 'blue')
plt.xlabel('No. of Confirmed cases', fontsize = 18)
plt.ylabel('States/UT', fontsize = 18)
plt.gca().invert_yaxis()   # this is to maintain the order in which the states appear
plt.xticks(fontsize = 14) 
plt.yticks(fontsize = 14)
plt.title('Total Confirmed Cases Statewise', fontsize = 20)

for index, value in enumerate(state_data["Confirmed"]):
    plt.text(value, index, str(value), fontsize = 12, verticalalignment = 'center')
plt.show()  


# donut chart representing nationwide total confirmed, cured and deceased cases
group_size = [sum(state_data['Confirmed']), 
              sum(state_data['Recovered']), 
              sum(state_data['Deceased'])]

group_labels = ['Confirmed\n' + str(sum(state_data['Confirmed'])), 
                'Recovered\n' + str(sum(state_data['Recovered'])), 
                'Deceased\n'  + str(sum(state_data['Deceased']))]
custom_colors = ['skyblue','yellowgreen','tomato']

plt.figure(figsize = (5,5))
plt.pie(group_size, labels = group_labels, colors = custom_colors)
central_circle = plt.Circle((0,0), 0.5, color = 'white')
fig = plt.gcf()
fig.gca().add_artist(central_circle)
plt.rc('font', size = 12) 
plt.title('Nationwide total Confirmed, Recovered and Deceased Cases', fontsize = 16)
plt.show()