This is the Table:
| NAME: | DATE: |
|---|---|
| Apple | 2022-10-04 |
| Apple | 2022-10-04 |
| Apple | 2022-10-04 |
| Orange | 2022-10-04 |
| Apple | 2022-10-06 |
| Apple | 2022-10-06 |
| Apple | 2022-10-06 |
I would like to group by name & date, and also add a column called 'Counts'.
OUTCOME that I wanna look like:
| NAME: | DATE: | COUNTS: |
|---|---|---|
| Apple | 2022-10-04 | 3 |
| Orange | 2022-10-04 | 1 |
| Apple | 2022-10-06 | 3 |
CodePudding user response：
One way to do it:
df.groupby(['NAME', 'DATE']).DATE.agg('count').to_frame('COUNTS').reset_index()
Output:
NAME DATE COUNTS
0 apple 2022-10-04 3
1 apple 2022-10-06 3
2 orange 2022-10-04 1
CodePudding user response：
Another possible solution:
df.value_counts(['NAME', 'DATE']).rename('COUNTS').reset_index()
Output:
NAME DATE COUNTS
0 Apple 2022-10-04 3
1 Apple 2022-10-06 3
2 Orange 2022-10-04 1