South Asia COVID-19 Growth Analysis

dataId countryCode2 \ 0 6bf1e47a-cfde-414a-91a3-4eafa13bef26 AF 1 6bf1e47a-cfde-414a-91a3-4eafa13bef26 AF 2 6bf1e47a-cfde-414a-91a3-4eafa13bef26 AF 3 6bf1e47a-cfde-414a-91a3-4eafa13bef26 AF 4 6bf1e47a-cfde-414a-91a3-4eafa13bef26 AF ... ... ... 21269 6bf1e47a-cfde-414a-91a3-4eafa13bef26 ZW 21270 6bf1e47a-cfde-414a-91a3-4eafa13bef26 ZW 21271 6bf1e47a-cfde-414a-91a3-4eafa13bef26 ZW 21272 6bf1e47a-cfde-414a-91a3-4eafa13bef26 ZW 21273 6bf1e47a-cfde-414a-91a3-4eafa13bef26 ZW date cases dailyCases 0 2019-12-31 00:00:00+00:00 0 0 1 2020-01-01 00:00:00+00:00 0 0 2 2020-01-02 00:00:00+00:00 0 0 3 2020-01-03 00:00:00+00:00 0 0 4 2020-01-04 00:00:00+00:00 0 0 ... ... ... ... 21269 2020-05-31 00:00:00+00:00 174 14 21270 2020-06-01 00:00:00+00:00 178 4 21271 2020-06-02 00:00:00+00:00 203 25 21272 2020-06-03 00:00:00+00:00 206 3 21273 2020-06-04 00:00:00+00:00 222 16 [21274 rows x 5 columns]

cases dailyCases countryCode2 date AD 2020-03-03 00:00:00+00:00 1 1 2020-03-14 00:00:00+00:00 2 1 2020-03-16 00:00:00+00:00 5 3 2020-03-17 00:00:00+00:00 14 9 2020-03-18 00:00:00+00:00 14 0 ... ... ... ZW 2020-05-31 00:00:00+00:00 174 14 2020-06-01 00:00:00+00:00 178 4 2020-06-02 00:00:00+00:00 203 25 2020-06-03 00:00:00+00:00 206 3 2020-06-04 00:00:00+00:00 222 16 [21274 rows x 2 columns]