StateWiseCovidAnalysis.py

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import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import plotly
import plotly.express as px

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state_df = pd.read_csv('./StatewiseTestingDetails.csv')
country_df = pd.read_csv('./covid_19_india.csv')

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country_df

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country_df.isnull().sum()

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country_df = country_df.drop(['Time','Sno','ConfirmedIndianNational', 'ConfirmedForeignNational'], axis=1)
country_df

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country_df['Active'] = country_df['Confirmed'] - country_df['Cured'] - country_df['Deaths']
country_df.tail() 

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country_df['Date'] = pd.to_datetime(country_df['Date'])

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country_df.head()

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fig=plt.figure(figsize=(15,18))
ax=sns.lineplot(data=country_df,x='Date',y='Active',hue='State/UnionTerritory')
ax.set_title("Active cases by States", size=20)
plt.show()

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fig=plt.figure(figsize=(15,8))
ax=sns.lineplot(data=country_df[country_df['State/UnionTerritory'].isin(['Kerala'])],x='Date',y='Active',hue='State/UnionTerritory')
ax.set_title("Active cases by States", size=20)
plt.show()

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india_cases.head()

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top_10_death_states = india_cases.sort_values('Deaths',ascending = False)[:10]
fig=plt.figure(figsize=(15,8))
plt.title("Top 10 States with highest number of death", size=20)
plt.xlabel("states")
plt.ylabel("Number of deaths in thousands")
ax=sns.barplot(data=top_10_death_states.iloc[:10],y=top_10_death_states.Deaths,x=top_10_death_states.index, linewidth=2, edgecolor='black').set(xlabel='States', ylabel='Number of deaths')
plt.show()

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top_10_cured_cases = india_cases.sort_values('Cured',ascending = False)[:10]
fig=plt.figure(figsize=(15,8))
plt.title("Top 10 States with highest number of cured cases", size=20)
plt.xlabel("states")
plt.ylabel("Number of cured cases")
ax=sns.barplot(data=top_10_cured_cases.iloc[:10],y=top_10_cured_cases.Cured,x=top_10_cured_cases.index, linewidth=2, edgecolor='black').set(xlabel='States', ylabel='Number of confirmed cases')
plt.show()

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