In this article, we will collect latest updated information about the coronavirus cases across the world and in a particular country. We will plot graphs to visualise the growth of total number of cases and the total deaths for the last 20 days. The latest data is fetched from Our World in Data.
Python modules required
- requests:
The requests library is used for making HTTP requests in Python.pip install requests
- matplotlib:
matplotlib is a comprehensive library for creating various types of graphs and interactive visualisations in Python.pip install matplotlib
Explanation:
The data scraped from the website(using requests), is converted to the csv-like format. Then this data is filtered to get the required statistics for the last 20 days and the visualizations are plotted(using matplotlib).
Below is the implementation.
from matplotlib import pyplot as plt import requests # function to plot data for country # and world def Plot(country): # getting request from the url req.raise_for_status() # converting to text and splitting # the rows of the csv data cf = req.text.split('\n') # converting to 2 dimensional list for i in range(len(cf)): cf[i]= cf[i].split(', ') dates =[] total =[] total_w =[] deaths =[] deaths_w =[] l =[] f = 0 for i in range(len(cf)-1): l = cf[i] c = l[1] # filtering data for a particular country if c == country: f = 1 # getting the dates, total cases and # deaths for the particular country dates.append(l[0][5:]) total.append(int(l[4])) deaths.append(int(l[5])) # filtering data for the world if c =='World': # getting total cases and deaths for # the world total_w.append(int(l[4])) deaths_w.append(int(l[5])) if f == 0: print("Invalid country name.") return # Plotting country data total_ax = plt.subplot(2, 2, 1) total_ax.set_title(country+' (Total Cases)') # plotting the curve for total cases total_ax.plot(dates[-20:], total[-20:]) # plotting the bars for total cases total_ax.bar(dates[-20:], total[-20:], alpha = 0.5) total_ax.set_xlabel("Date") plt.xticks(rotation = 45) death_ax = plt.subplot(2, 2, 2) death_ax.set_title(country+' (Total Deaths)') # plotting the curve for deaths death_ax.plot(dates[-20:], deaths[-20:], color ='red') # plotting the bars for deaths death_ax.bar(dates[-20:], deaths[-20:], color ='red', alpha = 0.5) death_ax.set_xlabel("Date") plt.xticks(rotation = 45) # Plotting world data total_w_ax = plt.subplot(2, 2, 3) total_w_ax.set_title('World (Total Cases)') # plotting the curve for total cases total_w_ax.plot(dates[-20:], total_w[-20:]) # plotting the bar for total cases total_w_ax.bar(dates[-20:], total_w[-20:], alpha = 0.5) total_w_ax.set_xlabel("Date") plt.xticks(rotation = 45) death_w_ax = plt.subplot(2, 2, 4) death_w_ax.set_title('World (Total Deaths)') # plotting the curve for deaths death_w_ax.plot(dates[-20:], deaths_w[-20:], color ='red') # plotting the curve for deaths death_w_ax.bar(dates[-20:], deaths_w[-20:], color ='red', alpha = 0.5) death_w_ax.set_xlabel("Date") plt.xticks(rotation = 45) plt.tight_layout() print("Enter country name...") country = input().title() Plot(country) plt.show() |
Input :
Enter country name... India
Output :
Input :
Enter country name... Italy
Output :
