Impact of Corona Virus on India
Exploratory data analysis using various python libraries.
With over 5.3 million cases, India is amongst the worst countries hit by the corona virus. The death toll in india has exceeded over 85,000.
As a data science enthusiast, i decided to explore the various factors because of which corona virus is spreading throughout the country. With the help of this dataset https://www.kaggle.com/sudalairajkumar/covid19-in-india I was able to make some predictions regarding these factors.
Importing the libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import cufflinks as cf
cf.go_offline()
%matplotlib inline
import plotly_express as px
import plotly.graph_objects as go
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
init_notebook_mode(connected=True)
import datetime
from IPython.display import HTMLReading the data
As all of the data was in CSV format it was quite easy to just read it in through pandas library.
Exploratory data analysis
Various plots were plotted with seaborn library.
It was seen that majority of people who were affected were in the 20–50 age group.
Nearly 67% of the pateints were males.
The above image shows the state-wise distribution. Maharashtra was most effected state in the country.
In summary, we have shown some simple yet detailed visualizations and animations in the full code.
The complete code for this article is available at :
