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i have this following data:

Date_reported Country_code Country WHO_region New_cases Cumulative_cases New_deaths Cumulative_deaths
0   2020-01-03  AF  Afghanistan EMRO    0   0   0   0
1   2020-01-04  AF  Afghanistan EMRO    0   0   0   0
2   2020-01-05  AF  Afghanistan EMRO    0   0   0   0
3   2020-01-06  AF  Afghanistan EMRO    0   0   0   0
4   2020-01-07  AF  Afghanistan EMRO    0   0   0   0
... ... ... ... ... ... ... ... ...
243868  2022-10-23  ZW  Zimbabwe    AFRO    0   257893  0   5606
243869  2022-10-24  ZW  Zimbabwe    AFRO    0   257893  0   5606
243870  2022-10-25  ZW  Zimbabwe    AFRO    0   257893  0   5606
243871  2022-10-26  ZW  Zimbabwe    AFRO    0   257893  0   5606
243872  2022-10-27  ZW  Zimbabwe    AFRO    0   257893  0   5606

i want to merge the all the country into a table like:

Date_reported New_cases Cumulative_cases New_deaths Cumulative_deaths
0   2020-01-03  0   0   0   0
1   2020-01-04  0   0   0   0
2   2020-01-05  0   0   0   0
3   2020-01-06  0   0   0   0
4   2020-01-07  0   0   0   0
... ... ... ... ... ... ... ... ...
243872  2022-10-27  sum  of  all    country

how can i use pandas to do it?

IsaacMak
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1 Answers1

2

You want to group the data by the date column and then sum each column:

df.groupby(['Date_reported'])['New_cases', 'Cumulative_cases', 'New_deaths', 'Cumulative_deaths'].sum()
richardjmorton
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