<jupyter_start><jupyter_text>Covid-19 short Data Analysis<jupyter_code>import pandas as pd
data = pd.read_csv(r'C:\Users\Adin\Desktop\MECHANISM\Covid-19 Dataset.csv')
data
data.count()
data.isnull()
data.isnull().sum()
import seaborn as sns

import matplotlib.pyplot as plt
sns.heatmap(data.isnull())
plt.show()<jupyter_output><empty_output><jupyter_text>Data Cleaning<jupyter_code>data.dropna(subset=['State'],inplace =True)
data.head()<jupyter_output><empty_output><jupyter_text>Plotting Scatter plot Confirmed Vs Deaths<jupyter_code>from matplotlib import rcParams
rcParams['figure.figsize']=8,6
data.plot(x='Confirmed',y='Deaths',style='o')
plt.xlabel('CONFIRMED CASES')
plt.ylabel('DEATHS')
plt.title('Scatter plot of Confirmed cases vs Deaths')
plt.show()<jupyter_output><empty_output><jupyter_text>Q1 (Groupby) (Show the number of confirmed, deaths and recovered in each region)<jupyter_code>data.head(2)
data.groupby('Region').sum()
# Checking Recovered only in descending order
data.groupby('Region')['Recovered'].sum().sort_values(ascending=False)<jupyter_output><empty_output><jupyter_text>Q2 Remove the records where confirmed is less than 10<jupyter_code>data.head(2)
data = data[~data['Confirmed']<10]
data<jupyter_output><empty_output><jupyter_text>Q3 Show the maximum number of confirmed cases in which region<jupyter_code>data.groupby('Region')['Confirmed'].sum().sort_values(ascending=False)<jupyter_output><empty_output><jupyter_text>Q4 Show the minimum number of Death cases in which region<jupyter_code>data.groupby('Region')['Deaths'].sum().sort_values(ascending=True)<jupyter_output><empty_output><jupyter_text>Q5 How many Confirmed, Deaths & Recovered cases were reported India till 29 April 2020<jupyter_code>data.head(2)
data[data.Region=='India']<jupyter_output><empty_output><jupyter_text>Q6 Sort the confirmed case coloumn in descending order<jupyter_code>data.sort_values(by='Confirmed', ascending=False)<jupyter_output><empty_output>
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