In [1]:
%run covid-19-data.ipynb
import pandas as pd
import numpy as np
import cufflinks as cf
| Country/Region | US | India | Brazil | Russia | France | Spain | Argentina | Colombia | United Kingdom | Mexico |
|---|---|---|---|---|---|---|---|---|---|---|
| 1/22/20 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1/23/20 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1/24/20 | 2 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 |
| 1/25/20 | 2 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 0 |
| 1/26/20 | 5 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 10/28/20 | 8856413 | 8040203 | 5468270 | 1553028 | 1280215 | 1136503 | 1130533 | 1041935 | 945378 | 906863 |
| 10/29/20 | 8944934 | 8088851 | 5494376 | 1570446 | 1327852 | 1160083 | 1143800 | 1053122 | 968456 | 912811 |
| 10/30/20 | 9044255 | 8137119 | 5516658 | 1588433 | 1377347 | 1185678 | 1157179 | 1063151 | 992874 | 918811 |
| 10/31/20 | 9133381 | 8184082 | 5535605 | 1606267 | 1412709 | 1185678 | 1166924 | 1074184 | 1014793 | 924962 |
| 11/1/20 | 9206975 | 8229313 | 5545705 | 1624648 | 1458999 | 1185678 | 1173533 | 1083321 | 1038054 | 929392 |
285 rows × 10 columns
In [2]:
# Time series total confirmed by country
fig = df_confirmed.iplot(asFigure=True, xTitle="Date", yTitle="Number", title=f'Logarithmic COVID-19 time series total confirmed by country as of {confirmed_latest}',logy=True)
fig.show()
In [3]:
# Time series total deaths by country
fig = df_deaths.iplot(asFigure=True, xTitle="Date", yTitle="Number", title=f'Logarithmic COVID-19 time series total deaths by country as of {deaths_latest}',logy=True)
fig.show()
In [4]:
# Time series total recovered by country
fig = df_recovered.iplot(asFigure=True, xTitle="Date", yTitle="Number", title=f'Logarithmic COVID-19 time series total recovered by country as of {recovered_latest}',logy=True)
fig.show()
In [5]:
# Total confirmed by date
fig = df_confirmed_total.iplot(asFigure=True, xTitle="Date", yTitle="Number", title=f'Logarithmic COVID-19 time series total confirmed as of {confirmed_latest}',logy=True)
fig.show()
In [6]:
# Total deaths by date (Logarithmic)
fig = df_deaths_total.iplot(asFigure=True, xTitle="Date", yTitle="Number", title=f'Logarithmic COVID-19 time series total deaths as of {deaths_latest}',logy=True)
fig.show()
In [7]:
# Total recovered by date
fig = df_recovered_total.iplot(asFigure=True, xTitle="Date", yTitle="Number", title=f'COVID-19 time series total confirmed as of {recovered_latest}',logy=True)
fig.show()