I have a df for the month of January with a Date and Time column.
| Date | Time | Global_active_power |
|---|---|---|
| 1/1/07 | 0:00:00 | 2.58 |
| 1/1/07 | 0:01:00 | 2.52 |
| 1/1/07 | 0:02:00 | 2.55 |
It continues in this pattern till the final day/time of the month.
I used to following code to try and group the Dates together and sum the Global_active_power for each day.
`jan_df = jan_df.drop(columns=['Time'])
new_df = jan_df.groupby(['Date']).sum()`
I get the following output:
| Date | Global_active_power |
|---|---|
| 1/1/07 | 2749.36 |
| 1/2/07 | 0 |
| 1/3/07 | 1480.43 |
This dataframe goes until the last date of the month, 1/31/07
I am confused why certain days have a 0 for the value as I know that the sum should be higher than 0. For instance 1/2/07 shows 0 for global_active
I am expecting a dataframe with a row for each day of the month and the global_active values should all be higher than 0
source https://stackoverflow.com/questions/75990010/python-pandas-groupby-not-working-as-intended
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