My df looks like this
Date | Col | Col1 |
---|---|---|
01/01/2022 | A | 500 |
01/01/2022 | B | 100 |
01/01/2022 | C | 400 |
02/01/2022 | A | 400 |
02/01/2022 | B | 150 |
02/01/2022 | C | 450 |
My desired output looks like
Date | Total |
---|---|
01/01/2022 | 1000 |
02/01/2022 | 1000 |
Please help. I wanna do it automatically (not manually-hardcoded)
I am trying this
df.groupby('Date')['Col1'].sum()
CodePudding user response:
Try just summing the entire group, rather than a specific column:
df.groupby('Date').sum()
CodePudding user response:
If you need totals and the separate column values for a given date, follow this general format.
needed_columnms = ['List','Of','Needed','Columns']
df_sums = df.groupby('Date')[needed_columns].sum()
df_sums['Total'] = df_sums[needed_columns].sum(1)
df_sums will provide you with a column total and grand total for each of the dates within 'Date'.