
fig = plt.figure(figsize = (19,10))
plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=1.0, wspace=0.4)

plt.subplot(4,4,1)
plt.scatter(df['new_cases'],df['new_cases'])
plt.xlabel('new cases')
plt.ylabel('new_cases')
plt.subplot(4,4,2)
plt.scatter(df['new_cases'],df['total_deaths'])
plt.xlabel('total_deaths')
plt.ylabel('new_cases')
plt.subplot(4,4,3)
plt.scatter(df['new_cases'],df['new_deaths'])
plt.xlabel('new_deaths')
plt.ylabel('new_cases')
plt.subplot(4,4,4)
plt.scatter(df['new_cases'],df['total_cases_per_million'])
plt.xlabel('total_cases_per_million')
plt.ylabel('new_cases')
plt.subplot(4,4,5)
plt.scatter(df['new_cases'],df['new_cases_per_million'])
plt.xlabel('new_cases_per_million')
plt.ylabel('new_cases')
plt.subplot(4,4,6)
plt.scatter(df['new_cases'],df['total_deaths_per_million'])
plt.xlabel('total_deaths_per_million')
plt.ylabel('new_cases')
plt.subplot(4,4,7)
plt.scatter(df['new_cases'],df['new_deaths_per_million'])
plt.xlabel('new_deaths_per_million')
plt.ylabel('new_cases')
plt.subplot(4,4,8)
plt.scatter(df['new_cases'],df['total_tests'])
plt.xlabel('total_tests')
plt.ylabel('new_cases')
plt.subplot(4,4,9)
plt.scatter(df['new_cases'],df['new_tests'])
plt.xlabel('new_tests')
plt.ylabel('new_cases')
plt.subplot(4,4,10)
plt.scatter(df['new_cases'],df['total_tests_per_thousand'])
plt.xlabel('total_tests_per_thousand')
plt.ylabel('new_cases')
plt.subplot(4,4,11)
plt.scatter(df['new_cases'],df['new_tests_per_thousand'])
plt.xlabel('new_tests_per_thousand')
plt.ylabel('new_cases')
plt.subplot(4,4,12)
plt.scatter(df['new_cases'],df['new_tests_smoothed'])
plt.xlabel('new_tests_smoothed')
plt.ylabel('new_cases')
plt.subplot(4,4,13)
plt.scatter(df['new_cases'],df['new_tests_smoothed_per_thousand'])
plt.xlabel('new_tests_smoothed_per_thousand')
plt.ylabel('new_cases')
plt.subplot(4,4,14)
plt.scatter(df['new_cases'],df['stringency_index'])
plt.xlabel('stringency_index')
plt.ylabel('new_cases')
plt.subplot(4,4,15)
plt.scatter(df['new_cases'],df['total_cases'])
plt.xlabel('total_cases')
plt.ylabel('new_cases')



#Scatterplot for total_deaths
fig = plt.figure(figsize = (19,10))
plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=1.0, wspace=0.4)

plt.subplot(4,4,1)
plt.scatter(df['total_deaths'],df['new_cases'])
plt.xlabel('new cases')
plt.ylabel('total_deaths')
plt.subplot(4,4,2)
plt.scatter(df['total_deaths'],df['total_deaths'])
plt.xlabel('total_deaths')
plt.ylabel('total_deaths')
plt.subplot(4,4,3)
plt.scatter(df['total_deaths'],df['new_deaths'])
plt.xlabel('new_deaths')
plt.ylabel('total_deaths')
plt.subplot(4,4,4)
plt.scatter(df['total_deaths'],df['total_cases_per_million'])
plt.xlabel('total_cases_per_million')
plt.ylabel('total_deaths')
plt.subplot(4,4,5)
plt.scatter(df['total_deaths'],df['new_cases_per_million'])
plt.xlabel('new_cases_per_million')
plt.ylabel('total_deaths')
plt.subplot(4,4,6)
plt.scatter(df['total_deaths'],df['total_deaths_per_million'])
plt.xlabel('total_deaths_per_million')
plt.ylabel('total_deaths')
plt.subplot(4,4,7)
plt.scatter(df['total_deaths'],df['new_deaths_per_million'])
plt.xlabel('new_deaths_per_million')
plt.ylabel('total_deaths')
plt.subplot(4,4,8)
plt.scatter(df['total_deaths'],df['total_tests'])
plt.xlabel('total_tests')
plt.ylabel('total_deaths')
plt.subplot(4,4,9)
plt.scatter(df['total_deaths'],df['new_tests'])
plt.xlabel('new_tests')
plt.ylabel('total_deaths')
plt.subplot(4,4,10)
plt.scatter(df['total_deaths'],df['total_tests_per_thousand'])
plt.xlabel('total_tests_per_thousand')
plt.ylabel('total_deaths')
plt.subplot(4,4,11)
plt.scatter(df['total_deaths'],df['new_tests_per_thousand'])
plt.xlabel('new_tests_per_thousand')
plt.ylabel('total_deaths')
plt.subplot(4,4,12)
plt.scatter(df['total_deaths'],df['new_tests_smoothed'])
plt.xlabel('new_tests_smoothed')
plt.ylabel('total_deaths')
plt.subplot(4,4,13)
plt.scatter(df['total_deaths'],df['new_tests_smoothed_per_thousand'])
plt.xlabel('new_tests_smoothed_per_thousand')
plt.ylabel('total_deaths')
plt.subplot(4,4,14)
plt.scatter(df['total_deaths'],df['stringency_index'])
plt.xlabel('stringency_index')
plt.ylabel('total_deaths')
plt.subplot(4,4,15)
plt.scatter(df['total_deaths'],df['total_cases'])
plt.xlabel('total_cases')
plt.ylabel('total_deaths')


#Scatterplot for NEW_deaths
fig = plt.figure(figsize = (19,10))
plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=1.0, wspace=0.4)

plt.subplot(4,4,1)
plt.scatter(df['new_deaths'],df['new_cases'])
plt.xlabel('new cases')
plt.ylabel('new_deaths')
plt.subplot(4,4,2)
plt.scatter(df['new_deaths'],df['total_deaths'])
plt.xlabel('total_deaths')
plt.ylabel('new_deaths')
plt.subplot(4,4,3)
plt.scatter(df['new_deaths'],df['new_deaths'])
plt.xlabel('new_deaths')
plt.ylabel('new_deaths')
plt.subplot(4,4,4)
plt.scatter(df['new_deaths'],df['total_cases_per_million'])
plt.xlabel('total_cases_per_million')
plt.ylabel('new_deaths')
plt.subplot(4,4,5)
plt.scatter(df['new_deaths'],df['new_cases_per_million'])
plt.xlabel('new_cases_per_million')
plt.ylabel('new_deaths')
plt.subplot(4,4,6)
plt.scatter(df['new_deaths'],df['total_deaths_per_million'])
plt.xlabel('total_deaths_per_million')
plt.ylabel('new_deaths')
plt.subplot(4,4,7)
plt.scatter(df['new_deaths'],df['new_deaths_per_million'])
plt.xlabel('new_deaths_per_million')
plt.ylabel('new_deaths')
plt.subplot(4,4,8)
plt.scatter(df['new_deaths'],df['total_tests'])
plt.xlabel('total_tests')
plt.ylabel('new_deaths')
plt.subplot(4,4,9)
plt.scatter(df['new_deaths'],df['new_tests'])
plt.xlabel('new_tests')
plt.ylabel('new_deaths')
plt.subplot(4,4,10)
plt.scatter(df['new_deaths'],df['total_tests_per_thousand'])
plt.xlabel('total_tests_per_thousand')
plt.ylabel('new_deaths')
plt.subplot(4,4,11)
plt.scatter(df['new_deaths'],df['new_tests_per_thousand'])
plt.xlabel('new_tests_per_thousand')
plt.ylabel('new_deaths')
plt.subplot(4,4,12)
plt.scatter(df['new_deaths'],df['new_tests_smoothed'])
plt.xlabel('new_tests_smoothed')
plt.ylabel('new_deaths')
plt.subplot(4,4,13)
plt.scatter(df['new_deaths'],df['new_tests_smoothed_per_thousand'])
plt.xlabel('new_tests_smoothed_per_thousand')
plt.ylabel('new_deaths')
plt.subplot(4,4,14)
plt.scatter(df['new_deaths'],df['stringency_index'])
plt.xlabel('stringency_index')
plt.ylabel('new_deaths')
plt.subplot(4,4,15)
plt.scatter(df['new_deaths'],df['total_cases'])
plt.xlabel('total_cases')
plt.ylabel('new_deaths')


#Scatter for total_cases_per_million
fig = plt.figure(figsize = (19,10))
plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=1.0, wspace=0.4)

plt.subplot(4,4,1)
plt.scatter(df['total_cases_per_million'],df['new_cases'])
plt.xlabel('new cases')
plt.ylabel('total_cases_per_million')
plt.subplot(4,4,2)
plt.scatter(df['total_cases_per_million'],df['total_deaths'])
plt.xlabel('total_deaths')
plt.ylabel('total_cases_per_million')
plt.subplot(4,4,3)
plt.scatter(df['total_cases_per_million'],df['new_deaths'])
plt.xlabel('new_deaths')
plt.ylabel('total_cases_per_million')
plt.subplot(4,4,4)
plt.scatter(df['total_cases_per_million'],df['total_cases_per_million'])
plt.xlabel('total_cases_per_million')
plt.ylabel('total_cases_per_million')
plt.subplot(4,4,5)
plt.scatter(df['total_cases_per_million'],df['new_cases_per_million'])
plt.xlabel('new_cases_per_million')
plt.ylabel('total_cases_per_million')
plt.subplot(4,4,6)
plt.scatter(df['total_cases_per_million'],df['total_deaths_per_million'])
plt.xlabel('total_deaths_per_million')
plt.ylabel('total_cases_per_million')
plt.subplot(4,4,7)
plt.scatter(df['total_cases_per_million'],df['new_deaths_per_million'])
plt.xlabel('new_deaths_per_million')
plt.ylabel('total_cases_per_million')
plt.subplot(4,4,8)
plt.scatter(df['total_cases_per_million'],df['total_tests'])
plt.xlabel('total_tests')
plt.ylabel('total_cases_per_million')
plt.subplot(4,4,9)
plt.scatter(df['total_cases_per_million'],df['new_tests'])
plt.xlabel('new_tests')
plt.ylabel('total_cases_per_million')
plt.subplot(4,4,10)
plt.scatter(df['total_cases_per_million'],df['total_tests_per_thousand'])
plt.xlabel('total_tests_per_thousand')
plt.ylabel('total_cases_per_million')
plt.subplot(4,4,11)
plt.scatter(df['total_cases_per_million'],df['new_tests_per_thousand'])
plt.xlabel('new_tests_per_thousand')
plt.ylabel('total_cases_per_million')
plt.subplot(4,4,12)
plt.scatter(df['total_cases_per_million'],df['new_tests_smoothed'])
plt.xlabel('new_tests_smoothed')
plt.ylabel('total_cases_per_million')
plt.subplot(4,4,13)
plt.scatter(df['total_cases_per_million'],df['new_tests_smoothed_per_thousand'])
plt.xlabel('new_tests_smoothed_per_thousand')
plt.ylabel('total_cases_per_million')
plt.subplot(4,4,14)
plt.scatter(df['total_cases_per_million'],df['stringency_index'])
plt.xlabel('stringency_index')
plt.ylabel('total_cases_per_million')
plt.subplot(4,4,15)
plt.scatter(df['total_cases_per_million'],df['total_cases'])
plt.xlabel('total_cases')
plt.ylabel('total_cases_per_million')


#Scatterplot for new_cases_per_million
fig = plt.figure(figsize = (19,10))
plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=1.0, wspace=0.4)

plt.subplot(4,4,1)
plt.scatter(df['new_cases_per_million'],df['new_cases'])
plt.xlabel('new cases')
plt.ylabel('new_cases_per_million')
plt.subplot(4,4,2)
plt.scatter(df['new_cases_per_million'],df['total_deaths'])
plt.xlabel('total_deaths')
plt.ylabel('new_cases_per_million')
plt.subplot(4,4,3)
plt.scatter(df['new_cases_per_million'],df['new_deaths'])
plt.xlabel('new_deaths')
plt.ylabel('new_cases_per_million')
plt.subplot(4,4,4)
plt.scatter(df['new_cases_per_million'],df['total_cases_per_million'])
plt.xlabel('total_cases_per_million')
plt.ylabel('new_cases_per_million')
plt.subplot(4,4,5)
plt.scatter(df['new_cases_per_million'],df['new_cases_per_million'])
plt.xlabel('new_cases_per_million')
plt.ylabel('new_cases_per_million')
plt.subplot(4,4,6)
plt.scatter(df['new_cases_per_million'],df['total_deaths_per_million'])
plt.xlabel('total_deaths_per_million')
plt.ylabel('new_cases_per_million')
plt.subplot(4,4,7)
plt.scatter(df['new_cases_per_million'],df['new_deaths_per_million'])
plt.xlabel('new_deaths_per_million')
plt.ylabel('new_cases_per_million')
plt.subplot(4,4,8)
plt.scatter(df['new_cases_per_million'],df['total_tests'])
plt.xlabel('total_tests')
plt.ylabel('new_cases_per_million')
plt.subplot(4,4,9)
plt.scatter(df['new_cases_per_million'],df['new_tests'])
plt.xlabel('new_tests')
plt.ylabel('new_cases_per_million')
plt.subplot(4,4,10)
plt.scatter(df['new_cases_per_million'],df['total_tests_per_thousand'])
plt.xlabel('total_tests_per_thousand')
plt.ylabel('new_cases_per_million')
plt.subplot(4,4,11)
plt.scatter(df['new_cases_per_million'],df['new_tests_per_thousand'])
plt.xlabel('new_tests_per_thousand')
plt.ylabel('new_cases_per_million')
plt.subplot(4,4,12)
plt.scatter(df['new_cases_per_million'],df['new_tests_smoothed'])
plt.xlabel('new_tests_smoothed')
plt.ylabel('new_cases_per_million')
plt.subplot(4,4,13)
plt.scatter(df['new_cases_per_million'],df['new_tests_smoothed_per_thousand'])
plt.xlabel('new_tests_smoothed_per_thousand')
plt.ylabel('new_cases_per_million')
plt.subplot(4,4,14)
plt.scatter(df['new_cases_per_million'],df['stringency_index'])
plt.xlabel('stringency_index')
plt.ylabel('new_cases_per_million')
plt.subplot(4,4,15)
plt.scatter(df['new_cases_per_million'],df['total_cases'])
plt.xlabel('total_cases')
plt.ylabel('new_cases_per_million')


#Scatterplot for total_deaths_per_million
fig = plt.figure(figsize = (19,10))
plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=1.0, wspace=0.4)

plt.subplot(4,4,1)
plt.scatter(df['total_deaths_per_million'],df['new_cases'])
plt.xlabel('new cases')
plt.ylabel('total_deaths_per_million')
plt.subplot(4,4,2)
plt.scatter(df['total_deaths_per_million'],df['total_deaths'])
plt.xlabel('total_deaths')
plt.ylabel('total_deaths_per_million')
plt.subplot(4,4,3)
plt.scatter(df['total_deaths_per_million'],df['new_deaths'])
plt.xlabel('new_deaths')
plt.ylabel('total_deaths_per_million')
plt.subplot(4,4,4)
plt.scatter(df['total_deaths_per_million'],df['total_cases_per_million'])
plt.xlabel('total_cases_per_million')
plt.ylabel('total_deaths_per_million')
plt.subplot(4,4,5)
plt.scatter(df['total_deaths_per_million'],df['new_cases_per_million'])
plt.xlabel('new_cases_per_million')
plt.ylabel('total_deaths_per_million')
plt.subplot(4,4,6)
plt.scatter(df['total_deaths_per_million'],df['total_deaths_per_million'])
plt.xlabel('total_deaths_per_million')
plt.ylabel('total_deaths_per_million')
plt.subplot(4,4,7)
plt.scatter(df['total_deaths_per_million'],df['new_deaths_per_million'])
plt.xlabel('new_deaths_per_million')
plt.ylabel('total_deaths_per_million')
plt.subplot(4,4,8)
plt.scatter(df['total_deaths_per_million'],df['total_tests'])
plt.xlabel('total_tests')
plt.ylabel('total_deaths_per_million')
plt.subplot(4,4,9)
plt.scatter(df['total_deaths_per_million'],df['new_tests'])
plt.xlabel('new_tests')
plt.ylabel('total_deaths_per_million')
plt.subplot(4,4,10)
plt.scatter(df['total_deaths_per_million'],df['total_tests_per_thousand'])
plt.xlabel('total_tests_per_thousand')
plt.ylabel('total_deaths_per_million')
plt.subplot(4,4,11)
plt.scatter(df['total_deaths_per_million'],df['new_tests_per_thousand'])
plt.xlabel('new_tests_per_thousand')
plt.ylabel('total_deaths_per_million')
plt.subplot(4,4,12)
plt.scatter(df['total_deaths_per_million'],df['new_tests_smoothed'])
plt.xlabel('new_tests_smoothed')
plt.ylabel('total_deaths_per_million')
plt.subplot(4,4,13)
plt.scatter(df['total_deaths_per_million'],df['new_tests_smoothed_per_thousand'])
plt.xlabel('new_tests_smoothed_per_thousand')
plt.ylabel('total_deaths_per_million')
plt.subplot(4,4,14)
plt.scatter(df['total_deaths_per_million'],df['stringency_index'])
plt.xlabel('stringency_index')
plt.ylabel('total_deaths_per_million')
plt.subplot(4,4,15)
plt.scatter(df['total_deaths_per_million'],df['total_cases'])
plt.xlabel('total_cases')
plt.ylabel('total_deaths_per_million')


#Scatterplot for new_deaths_per_million
fig = plt.figure(figsize = (19,10))
plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=1.0, wspace=0.4)

plt.subplot(4,4,1)
plt.scatter(df['new_deaths_per_million'],df['new_cases'])
plt.xlabel('new cases')
plt.ylabel('new_deaths_per_million')
plt.subplot(4,4,2)
plt.scatter(df['new_deaths_per_million'],df['total_deaths'])
plt.xlabel('total_deaths')
plt.ylabel('new_deaths_per_million')
plt.subplot(4,4,3)
plt.scatter(df['new_deaths_per_million'],df['new_deaths'])
plt.xlabel('new_deaths')
plt.ylabel('new_deaths_per_million')
plt.subplot(4,4,4)
plt.scatter(df['new_deaths_per_million'],df['total_cases_per_million'])
plt.xlabel('total_cases_per_million')
plt.ylabel('new_deaths_per_million')
plt.subplot(4,4,5)
plt.scatter(df['new_deaths_per_million'],df['new_cases_per_million'])
plt.xlabel('new_cases_per_million')
plt.ylabel('new_deaths_per_million')
plt.subplot(4,4,6)
plt.scatter(df['new_deaths_per_million'],df['total_deaths_per_million'])
plt.xlabel('total_deaths_per_million')
plt.ylabel('new_deaths_per_million')
plt.subplot(4,4,7)
plt.scatter(df['new_deaths_per_million'],df['new_deaths_per_million'])
plt.xlabel('new_deaths_per_million')
plt.ylabel('new_deaths_per_million')
plt.subplot(4,4,8)
plt.scatter(df['new_deaths_per_million'],df['total_tests'])
plt.xlabel('total_tests')
plt.ylabel('new_deaths_per_million')
plt.subplot(4,4,9)
plt.scatter(df['new_deaths_per_million'],df['new_tests'])
plt.xlabel('new_tests')
plt.ylabel('new_deaths_per_million')
plt.subplot(4,4,10)
plt.scatter(df['new_deaths_per_million'],df['total_tests_per_thousand'])
plt.xlabel('total_tests_per_thousand')
plt.ylabel('new_deaths_per_million')
plt.subplot(4,4,11)
plt.scatter(df['new_deaths_per_million'],df['new_tests_per_thousand'])
plt.xlabel('new_tests_per_thousand')
plt.ylabel('new_deaths_per_million')
plt.subplot(4,4,12)
plt.scatter(df['new_deaths_per_million'],df['new_tests_smoothed'])
plt.xlabel('new_tests_smoothed')
plt.ylabel('new_deaths_per_million')
plt.subplot(4,4,13)
plt.scatter(df['new_deaths_per_million'],df['new_tests_smoothed_per_thousand'])
plt.xlabel('new_tests_smoothed_per_thousand')
plt.ylabel('new_deaths_per_million')
plt.subplot(4,4,14)
plt.scatter(df['new_deaths_per_million'],df['stringency_index'])
plt.xlabel('stringency_index')
plt.ylabel('new_deaths_per_million')
plt.subplot(4,4,15)
plt.scatter(df['new_deaths_per_million'],df['total_cases'])
plt.xlabel('total_cases')
plt.ylabel('new_deaths_per_million')


#Scatterplot for total_tests
fig = plt.figure(figsize = (19,10))
plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=1.0, wspace=0.4)

plt.subplot(4,4,1)
plt.scatter(df['total_tests'],df['new_cases'])
plt.xlabel('new cases')
plt.ylabel('total_tests')
plt.subplot(4,4,2)
plt.scatter(df['total_tests'],df['total_deaths'])
plt.xlabel('total_deaths')
plt.ylabel('total_tests')
plt.subplot(4,4,3)
plt.scatter(df['total_tests'],df['new_deaths'])
plt.xlabel('new_deaths')
plt.ylabel('total_tests')
plt.subplot(4,4,4)
plt.scatter(df['total_tests'],df['total_cases_per_million'])
plt.xlabel('total_cases_per_million')
plt.ylabel('total_tests')
plt.subplot(4,4,5)
plt.scatter(df['total_tests'],df['new_cases_per_million'])
plt.xlabel('new_cases_per_million')
plt.ylabel('total_tests')
plt.subplot(4,4,6)
plt.scatter(df['total_tests'],df['total_deaths_per_million'])
plt.xlabel('total_deaths_per_million')
plt.ylabel('total_tests')
plt.subplot(4,4,7)
plt.scatter(df['total_tests'],df['new_deaths_per_million'])
plt.xlabel('new_deaths_per_million')
plt.ylabel('total_tests')
plt.subplot(4,4,8)
plt.scatter(df['total_tests'],df['total_tests'])
plt.xlabel('total_tests')
plt.ylabel('total_tests')
plt.subplot(4,4,9)
plt.scatter(df['total_tests'],df['new_tests'])
plt.xlabel('new_tests')
plt.ylabel('total_tests')
plt.subplot(4,4,10)
plt.scatter(df['total_tests'],df['total_tests_per_thousand'])
plt.xlabel('total_tests_per_thousand')
plt.ylabel('total_tests')
plt.subplot(4,4,11)
plt.scatter(df['total_tests'],df['new_tests_per_thousand'])
plt.xlabel('new_tests_per_thousand')
plt.ylabel('total_tests')
plt.subplot(4,4,12)
plt.scatter(df['total_tests'],df['new_tests_smoothed'])
plt.xlabel('new_tests_smoothed')
plt.ylabel('total_tests')
plt.subplot(4,4,13)
plt.scatter(df['total_tests'],df['new_tests_smoothed_per_thousand'])
plt.xlabel('new_tests_smoothed_per_thousand')
plt.ylabel('total_tests')
plt.subplot(4,4,14)
plt.scatter(df['total_tests'],df['stringency_index'])
plt.xlabel('stringency_index')
plt.ylabel('total_tests')
plt.subplot(4,4,15)
plt.scatter(df['total_tests'],df['total_cases'])
plt.xlabel('total_cases')
plt.ylabel('total_tests')


#Scatterplot for new_tests
fig = plt.figure(figsize = (19,10))
plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=1.0, wspace=0.4)

plt.subplot(4,4,1)
plt.scatter(df['new_tests'],df['new_cases'])
plt.xlabel('new cases')
plt.ylabel('new_tests')
plt.subplot(4,4,2)
plt.scatter(df['new_tests'],df['total_deaths'])
plt.xlabel('total_deaths')
plt.ylabel('new_tests')
plt.subplot(4,4,3)
plt.scatter(df['new_tests'],df['new_deaths'])
plt.xlabel('new_deaths')
plt.ylabel('new_tests')
plt.subplot(4,4,4)
plt.scatter(df['new_tests'],df['total_cases_per_million'])
plt.xlabel('total_cases_per_million')
plt.ylabel('new_tests')
plt.subplot(4,4,5)
plt.scatter(df['new_tests'],df['new_cases_per_million'])
plt.xlabel('new_cases_per_million')
plt.ylabel('new_tests')
plt.subplot(4,4,6)
plt.scatter(df['new_tests'],df['total_deaths_per_million'])
plt.xlabel('total_deaths_per_million')
plt.ylabel('new_tests')
plt.subplot(4,4,7)
plt.scatter(df['new_tests'],df['new_deaths_per_million'])
plt.xlabel('new_deaths_per_million')
plt.ylabel('new_tests')
plt.subplot(4,4,8)
plt.scatter(df['new_tests'],df['total_tests'])
plt.xlabel('total_tests')
plt.ylabel('new_tests')
plt.subplot(4,4,9)
plt.scatter(df['new_tests'],df['new_tests'])
plt.xlabel('new_tests')
plt.ylabel('new_tests')
plt.subplot(4,4,10)
plt.scatter(df['new_tests'],df['total_tests_per_thousand'])
plt.xlabel('total_tests_per_thousand')
plt.ylabel('new_tests')
plt.subplot(4,4,11)
plt.scatter(df['new_tests'],df['new_tests_per_thousand'])
plt.xlabel('new_tests_per_thousand')
plt.ylabel('new_tests')
plt.subplot(4,4,12)
plt.scatter(df['new_tests'],df['new_tests_smoothed'])
plt.xlabel('new_tests_smoothed')
plt.ylabel('new_tests')
plt.subplot(4,4,13)
plt.scatter(df['new_tests'],df['new_tests_smoothed_per_thousand'])
plt.xlabel('new_tests_smoothed_per_thousand')
plt.ylabel('new_tests')
plt.subplot(4,4,14)
plt.scatter(df['new_tests'],df['stringency_index'])
plt.xlabel('stringency_index')
plt.ylabel('new_tests')
plt.subplot(4,4,15)
plt.scatter(df['new_tests'],df['total_cases'])
plt.xlabel('total_cases')
plt.ylabel('new_tests')






#Scatterplot for total_tests_per_thousand
fig = plt.figure(figsize = (19,10))
plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=1.0, wspace=0.4)

plt.subplot(4,4,1)
plt.scatter(df['total_tests_per_thousand'],df['new_cases'])
plt.xlabel('new cases')
plt.ylabel('total_tests_per_thousand')
plt.subplot(4,4,2)
plt.scatter(df['total_tests_per_thousand'],df['total_deaths'])
plt.xlabel('total_deaths')
plt.ylabel('total_tests_per_thousand')
plt.subplot(4,4,3)
plt.scatter(df['total_tests_per_thousand'],df['new_deaths'])
plt.xlabel('new_deaths')
plt.ylabel('total_tests_per_thousand')
plt.subplot(4,4,4)
plt.scatter(df['total_tests_per_thousand'],df['total_cases_per_million'])
plt.xlabel('total_cases_per_million')
plt.ylabel('total_tests_per_thousand')
plt.subplot(4,4,5)
plt.scatter(df['total_tests_per_thousand'],df['new_cases_per_million'])
plt.xlabel('new_cases_per_million')
plt.ylabel('total_tests_per_thousand')
plt.subplot(4,4,6)
plt.scatter(df['total_tests_per_thousand'],df['total_deaths_per_million'])
plt.xlabel('total_deaths_per_million')
plt.ylabel('total_tests_per_thousand')
plt.subplot(4,4,7)
plt.scatter(df['total_tests_per_thousand'],df['new_deaths_per_million'])
plt.xlabel('new_deaths_per_million')
plt.ylabel('total_tests_per_thousand')
plt.subplot(4,4,8)
plt.scatter(df['total_tests_per_thousand'],df['total_tests'])
plt.xlabel('total_tests')
plt.ylabel('total_tests_per_thousand')
plt.subplot(4,4,9)
plt.scatter(df['total_tests_per_thousand'],df['new_tests'])
plt.xlabel('new_tests')
plt.ylabel('total_tests_per_thousand')
plt.subplot(4,4,10)
plt.scatter(df['total_tests_per_thousand'],df['total_tests_per_thousand'])
plt.xlabel('total_tests_per_thousand')
plt.ylabel('total_tests_per_thousand')
plt.subplot(4,4,11)
plt.scatter(df['total_tests_per_thousand'],df['new_tests_per_thousand'])
plt.xlabel('new_tests_per_thousand')
plt.ylabel('total_tests_per_thousand')
plt.subplot(4,4,12)
plt.scatter(df['total_tests_per_thousand'],df['new_tests_smoothed'])
plt.xlabel('new_tests_smoothed')
plt.ylabel('total_tests_per_thousand')
plt.subplot(4,4,13)
plt.scatter(df['total_tests_per_thousand'],df['new_tests_smoothed_per_thousand'])
plt.xlabel('new_tests_smoothed_per_thousand')
plt.ylabel('total_tests_per_thousand')
plt.subplot(4,4,14)
plt.scatter(df['total_tests_per_thousand'],df['stringency_index'])
plt.xlabel('stringency_index')
plt.ylabel('total_tests_per_thousand')
plt.subplot(4,4,15)
plt.scatter(df['total_tests_per_thousand'],df['total_cases'])
plt.xlabel('total_cases')
plt.ylabel('total_tests_per_thousand')





#Scatterplot for new_tests_per_thousand
fig = plt.figure(figsize = (19,10))
plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=1.0, wspace=0.4)

plt.subplot(4,4,1)
plt.scatter(df['new_tests_per_thousand'],df['new_cases'])
plt.xlabel('new cases')
plt.ylabel('new_tests_per_thousand')
plt.subplot(4,4,2)
plt.scatter(df['new_tests_per_thousand'],df['total_deaths'])
plt.xlabel('total_deaths')
plt.ylabel('new_tests_per_thousand')
plt.subplot(4,4,3)
plt.scatter(df['new_tests_per_thousand'],df['new_deaths'])
plt.xlabel('new_deaths')
plt.ylabel('new_tests_per_thousand')
plt.subplot(4,4,4)
plt.scatter(df['new_tests_per_thousand'],df['total_cases_per_million'])
plt.xlabel('total_cases_per_million')
plt.ylabel('new_tests_per_thousand')
plt.subplot(4,4,5)
plt.scatter(df['new_tests_per_thousand'],df['new_cases_per_million'])
plt.xlabel('new_cases_per_million')
plt.ylabel('new_tests_per_thousand')
plt.subplot(4,4,6)
plt.scatter(df['new_tests_per_thousand'],df['total_deaths_per_million'])
plt.xlabel('total_deaths_per_million')
plt.ylabel('new_tests_per_thousand')
plt.subplot(4,4,7)
plt.scatter(df['new_tests_per_thousand'],df['new_deaths_per_million'])
plt.xlabel('new_deaths_per_million')
plt.ylabel('new_tests_per_thousand')
plt.subplot(4,4,8)
plt.scatter(df['new_tests_per_thousand'],df['total_tests'])
plt.xlabel('total_tests')
plt.ylabel('new_tests_per_thousand')
plt.subplot(4,4,9)
plt.scatter(df['new_tests_per_thousand'],df['new_tests'])
plt.xlabel('new_tests')
plt.ylabel('new_tests_per_thousand')
plt.subplot(4,4,10)
plt.scatter(df['new_tests_per_thousand'],df['total_tests_per_thousand'])
plt.xlabel('total_tests_per_thousand')
plt.ylabel('new_tests_per_thousand')
plt.subplot(4,4,11)
plt.scatter(df['new_tests_per_thousand'],df['new_tests_per_thousand'])
plt.xlabel('new_tests_per_thousand')
plt.ylabel('new_tests_per_thousand')
plt.subplot(4,4,12)
plt.scatter(df['new_tests_per_thousand'],df['new_tests_smoothed'])
plt.xlabel('new_tests_smoothed')
plt.ylabel('new_tests_per_thousand')
plt.subplot(4,4,13)
plt.scatter(df['new_tests_per_thousand'],df['new_tests_smoothed_per_thousand'])
plt.xlabel('new_tests_smoothed_per_thousand')
plt.ylabel('new_tests_per_thousand')
plt.subplot(4,4,14)
plt.scatter(df['new_tests_per_thousand'],df['stringency_index'])
plt.xlabel('stringency_index')
plt.ylabel('new_tests_per_thousand')
plt.subplot(4,4,15)
plt.scatter(df['new_tests_per_thousand'],df['total_cases'])
plt.xlabel('total_cases')
plt.ylabel('new_tests_per_thousand')


#Scatterplot for new_tests_smoothed
fig = plt.figure(figsize = (19,10))
plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=1.0, wspace=0.4)

plt.subplot(4,4,1)
plt.scatter(df['new_tests_smoothed'],df['new_cases'])
plt.xlabel('new cases')
plt.ylabel('new_tests_smoothed')
plt.subplot(4,4,2)
plt.scatter(df['new_tests_smoothed'],df['total_deaths'])
plt.xlabel('total_deaths')
plt.ylabel('new_tests_smoothed')
plt.subplot(4,4,3)
plt.scatter(df['new_tests_smoothed'],df['new_deaths'])
plt.xlabel('new_deaths')
plt.ylabel('new_tests_smoothed')
plt.subplot(4,4,4)
plt.scatter(df['new_tests_smoothed'],df['total_cases_per_million'])
plt.xlabel('total_cases_per_million')
plt.ylabel('new_tests_smoothed')
plt.subplot(4,4,5)
plt.scatter(df['new_tests_smoothed'],df['new_cases_per_million'])
plt.xlabel('new_cases_per_million')
plt.ylabel('new_tests_smoothed')
plt.subplot(4,4,6)
plt.scatter(df['new_tests_smoothed'],df['total_deaths_per_million'])
plt.xlabel('total_deaths_per_million')
plt.ylabel('new_tests_smoothed')
plt.subplot(4,4,7)
plt.scatter(df['new_tests_smoothed'],df['new_deaths_per_million'])
plt.xlabel('new_deaths_per_million')
plt.ylabel('new_tests_smoothed')
plt.subplot(4,4,8)
plt.scatter(df['new_tests_smoothed'],df['total_tests'])
plt.xlabel('total_tests')
plt.ylabel('new_tests_smoothed')
plt.subplot(4,4,9)
plt.scatter(df['new_tests_smoothed'],df['new_tests'])
plt.xlabel('new_tests')
plt.ylabel('new_tests_smoothed')
plt.subplot(4,4,10)
plt.scatter(df['new_tests_smoothed'],df['total_tests_per_thousand'])
plt.xlabel('total_tests_per_thousand')
plt.ylabel('new_tests_smoothed')
plt.subplot(4,4,11)
plt.scatter(df['new_tests_smoothed'],df['new_tests_per_thousand'])
plt.xlabel('new_tests_per_thousand')
plt.ylabel('new_tests_smoothed')
plt.subplot(4,4,12)
plt.scatter(df['new_tests_smoothed'],df['new_tests_smoothed'])
plt.xlabel('new_tests_smoothed')
plt.ylabel('new_tests_smoothed')
plt.subplot(4,4,13)
plt.scatter(df['new_tests_smoothed'],df['new_tests_smoothed_per_thousand'])
plt.xlabel('new_tests_smoothed_per_thousand')
plt.ylabel('new_tests_smoothed')
plt.subplot(4,4,14)
plt.scatter(df['new_tests_smoothed'],df['stringency_index'])
plt.xlabel('stringency_index')
plt.ylabel('new_tests_smoothed')
plt.subplot(4,4,15)
plt.scatter(df['new_tests_smoothed'],df['total_cases'])
plt.xlabel('total_cases')
plt.ylabel('new_tests_smoothed')




#Scatterplot for new_tests_smoothed_per_thousand
fig = plt.figure(figsize = (19,10))
plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=1.0, wspace=0.4)

plt.subplot(4,4,1)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['new_cases'])
plt.xlabel('new cases')
plt.ylabel('new_tests_smoothed_per_thousand')
plt.subplot(4,4,2)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['total_deaths'])
plt.xlabel('total_deaths')
plt.ylabel('new_tests_smoothed_per_thousand')
plt.subplot(4,4,3)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['new_deaths'])
plt.xlabel('new_deaths')
plt.ylabel('new_tests_smoothed_per_thousand')
plt.subplot(4,4,4)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['total_cases_per_million'])
plt.xlabel('total_cases_per_million')
plt.ylabel('new_tests_smoothed_per_thousand')
plt.subplot(4,4,5)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['new_cases_per_million'])
plt.xlabel('new_cases_per_million')
plt.ylabel('new_tests_smoothed_per_thousand')
plt.subplot(4,4,6)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['total_deaths_per_million'])
plt.xlabel('total_deaths_per_million')
plt.ylabel('new_tests_smoothed_per_thousand')
plt.subplot(4,4,7)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['new_deaths_per_million'])
plt.xlabel('new_deaths_per_million')
plt.ylabel('new_tests_smoothed_per_thousand')
plt.subplot(4,4,8)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['total_tests'])
plt.xlabel('total_tests')
plt.ylabel('new_tests_smoothed_per_thousand')
plt.subplot(4,4,9)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['new_tests'])
plt.xlabel('new_tests')
plt.ylabel('new_tests_smoothed_per_thousand')
plt.subplot(4,4,10)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['total_tests_per_thousand'])
plt.xlabel('total_tests_per_thousand')
plt.ylabel('new_tests_smoothed_per_thousand')
plt.subplot(4,4,11)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['new_tests_per_thousand'])
plt.xlabel('new_tests_per_thousand')
plt.ylabel('new_tests_smoothed_per_thousand')
plt.subplot(4,4,12)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['new_tests_smoothed'])
plt.xlabel('new_tests_smoothed')
plt.ylabel('new_tests_smoothed_per_thousand')
plt.subplot(4,4,13)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['new_tests_smoothed_per_thousand'])
plt.xlabel('new_tests_smoothed_per_thousand')
plt.ylabel('new_tests_smoothed_per_thousand')
plt.subplot(4,4,14)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['stringency_index'])
plt.xlabel('stringency_index')
plt.ylabel('new_tests_smoothed_per_thousand')
plt.subplot(4,4,15)
plt.scatter(df['new_tests_smoothed_per_thousand'],df['total_cases'])
plt.xlabel('total_cases')
plt.ylabel('new_tests_smoothed_per_thousand')





#Scatterplot for stringency index
fig = plt.figure(figsize = (19,10))
plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=1.0, wspace=0.4)

plt.subplot(4,4,1)
plt.scatter(df['stringency_index'],df['new_cases'])
plt.xlabel('new cases')
plt.ylabel('stringency_index')
plt.subplot(4,4,2)
plt.scatter(df['stringency_index'],df['total_deaths'])
plt.xlabel('total_deaths')
plt.ylabel('stringency_index')
plt.subplot(4,4,3)
plt.scatter(df['stringency_index'],df['new_deaths'])
plt.xlabel('new_deaths')
plt.ylabel('stringency_index')
plt.subplot(4,4,4)
plt.scatter(df['stringency_index'],df['total_cases_per_million'])
plt.xlabel('total_cases_per_million')
plt.ylabel('stringency_index')
plt.subplot(4,4,5)
plt.scatter(df['stringency_index'],df['new_cases_per_million'])
plt.xlabel('new_cases_per_million')
plt.ylabel('stringency_index')
plt.subplot(4,4,6)
plt.scatter(df['stringency_index'],df['total_deaths_per_million'])
plt.xlabel('total_deaths_per_million')
plt.ylabel('stringency_index')
plt.subplot(4,4,7)
plt.scatter(df['stringency_index'],df['new_deaths_per_million'])
plt.xlabel('new_deaths_per_million')
plt.ylabel('stringency_index')
plt.subplot(4,4,8)
plt.scatter(df['stringency_index'],df['total_tests'])
plt.xlabel('total_tests')
plt.ylabel('stringency_index')
plt.subplot(4,4,9)
plt.scatter(df['stringency_index'],df['new_tests'])
plt.xlabel('new_tests')
plt.ylabel('stringency_index')
plt.subplot(4,4,10)
plt.scatter(df['stringency_index'],df['total_tests_per_thousand'])
plt.xlabel('total_tests_per_thousand')
plt.ylabel('stringency_index')
plt.subplot(4,4,11)
plt.scatter(df['stringency_index'],df['new_tests_per_thousand'])
plt.xlabel('new_tests_per_thousand')
plt.ylabel('stringency_index')
plt.subplot(4,4,12)
plt.scatter(df['stringency_index'],df['new_tests_smoothed'])
plt.xlabel('new_tests_smoothed')
plt.ylabel('stringency_index')
plt.subplot(4,4,13)
plt.scatter(df['stringency_index'],df['new_tests_smoothed_per_thousand'])
plt.xlabel('new_tests_smoothed_per_thousand')
plt.ylabel('stringency_index')
plt.subplot(4,4,14)
plt.scatter(df['stringency_index'],df['stringency_index'])
plt.xlabel('stringency_index')
plt.ylabel('stringency_index')
plt.subplot(4,4,15)
plt.scatter(df['stringency_index'],df['total_cases'])
plt.xlabel('total_cases')
plt.ylabel('stringency_index')






