Reputation: 11
Date frame having two categorical variable column with date time stamp.
Date | Time | Va | Vb |
---|---|---|---|
01-01-2023 | 05:55 | A | B |
01-01-2023 | 06:25 | A | |
01-01-2023 | 17:42 | B | |
01-01-2023 | 19:17 | A | B |
02-01-2023 | 05:55 | A | B |
02-01-2023 | 06:25 | A | B |
02-01-2023 | 17:42 | A | B |
02-01-2023 | 19:17 | A |
To group by the set by date and count Va and Vb for a date. Expected Result:
Va | Vb | |
---|---|---|
01-01-2023 | 3 | 3 |
02-01-2023 | 4 | 3 |
Wrote in previous slide
Upvotes: 1
Views: 37
Reputation: 195573
Try:
out = df[['Date', 'Va', 'Vb']].groupby('Date').count()
print(out)
Prints:
Va Vb
Date
01-01-2023 3 3
02-01-2023 4 3
Upvotes: 0
Reputation: 23837
If you are using an SQL database (and those empty values are NULL):
Select Date, Count(Va) as Va, Count(Vb) as Vb
from sourceTable
group by date;
Upvotes: 0