Python Code to Visualize COVID 19 data in a Bubble Map

By Kiran Reddy

In this project, we are going to learn how to 1) Web scrape COVID 19 data of India 2) Visualize it in a Bubble Map

Scraping the COVID 19 data

For this project, we will be scraping the Wikipedia page that contains the COVID 19 state-wise data of India.

Before Scraping let us import the required packages

import pandas as pd

# for getting India map

import folium

after importing the packages, read the CSV file containing the latitudes and longitudes of Indian states.

coordinates = pd.read_csv("latandlon.csv")

now we will scrape the COVID 19 data

# Retreving the LIVE COVID19 Stats from Wikipedia

coronastats = pd.read_html('https://en.wikipedia.org/wiki/COVID-19_pandemic_in_India#covid19-container',match='State/Union Territory')

# Convert to DataFrame

covid19 = pd.DataFrame(coronastats[0])

Cleaning the COVID 19 data

# cleaning Covid19 Dataframe
# Removing unnecessary rows at the tail and Unnecessary columns

covid19 = covid19.iloc[:-2,:-4]

# Renaming Attribute Names for simplicity

covid19.columns = ['State','Total cases','Deaths','Recoveries','Active cases']

# covid19.head()

covid19

the cleaned COVID 19 data looks like this

State	Total cases	Deaths	Recoveries	Active cases
0	Andaman and Nicobar Islands	4126	56	3892	178
1	Andhra Pradesh	786050	6453	744532	35065
2	Arunachal Pradesh	13643	30	10780	2833
3	Assam	201,407[b]	875	173213	27319
4	Bihar	205945	1003	194005	10937

Joining the two Data Frames

now we will merge/join the two data frames, one is the coordinates data frame and the other is the covid19 data frame

# joining/merging the two data frames


covid = covid19.join(coordinates.set_index('State'), on = 'State')

covid

after joining the two data frames we will store it in a covid data frame

the resultant data frame looks like this

	State	Total cases	Deaths	Recoveries	Active cases	Latitude	Longitude
0	Andaman and Nicobar Islands	4126	56	3892.0	178	11.667026	92.735983
1	Andhra Pradesh	786050	6453	744532.0	35065	17.686800	83.218500
2	Arunachal Pradesh	13643	30	10780.0	2833	27.100399	93.616601
3	Assam	201,407[b]	875	173213.0	27319	26.749981	94.216667
4	Bihar	205945	1003	194005.0	10937	25.785414	87.479973

Plotting The Bubble Map

now, before plotting the bubble map make sure that the column you are willing to plot should be of the float data type

for example, I'm plotting the recoveries of each state on the map

I'll be converting all entries in the recoveries column into the float datatype

covid19['Recoveries']=covid19.Recoveries.astype(float)

 

Initializing the map m1

 

# Make an empty map
m1 = folium.Map(location=[20.5937,78.9629], zoom_start=5)

 

convert each column data frame into the list

 

state = list(covid['State'])
latitude = list(covid['Latitude'])
longitude = list(covid['Longitude'])
total = list(covid['Total cases'])
deaths = list(covid['Deaths'])
recovery = list(covid['Recoveries'])
active = list(covid['Active cases'])

for s, lat, long, t, d, r, a in zip(state,latitude ,longitude ,total , deaths, recovery, active):
    folium.Circle(
        location=[lat, long],
        popup=folium.Popup(('State  : ' + s + ' 
' +
                            'Total Cases : ' + str(t) + '
' +
                            'Deaths : ' + str(d) + '
' +
                            'Recoveries : ' + str(r) + '
' +
                            'Active Cases : ' + str(a) + ''), max_width=200),
        radius=r * 0.2,
        color='green',
        fill=True,
        fill_color='green'
    ).add_to(m1)

since we are plotting recoveries of each state I'm using the Green color for Bubbles

you can save the plot in an HTML file

 

# Save it as html
m1.save('mymap.html')

Similarly, you can plot the Bubble Map for Deaths and Total Cases in India.

Try Hands-on this Data visualization

Happy Learning