I would like create a new column my dataset and insert a value in a specific row based ona few conditions.
I found this previous post that was helpful but it does not account for multiple conditions, just name == Tim. How to create a new column and insert value at a particular row in pandas dataframe?
DF:
| Date | Group | State | Count |
|---|---|---|---|
| 2021-01-01 | 001 | IL | 0 |
| 2021-01-01 | 002 | IL | 5 |
| 2021-01-02 | 001 | CA | 3 |
| 2021-01-02 | 002 | CA | 9 |
| 2021-01-03 | 001 | AZ | 2 |
| 2021-01-03 | 002 | AZ | 8 |
| 2021-01-04 | 001 | WY | 4 |
| 2021-01-04 | 002 | WY | 7 |
Desired Output:
DF:
| Date | Group | State | Count | Sub |
|---|---|---|---|---|
| 2021-01-01 | 001 | IL | 0 | 0 |
| 2021-01-01 | 002 | IL | 5 | 0 |
| 2021-01-02 | 001 | CA | 3 | 0 |
| 2021-01-02 | 002 | CA | 9 | 0 |
| 2021-01-03 | 001 | AZ | 2 | 0 |
| 2021-01-03 | 002 | AZ | 8 | 3 |
| 2021-01-04 | 001 | WY | 4 | 0 |
| 2021-01-04 | 002 | WY | 7 | 0 |
I would like insert the value '3' where Date == 2021-01-03 and group = 002 and state = 'AZ'.
EDIT: I cannot use the post that was linked to this question because the rows of this dataframe are updated everyday. As such, I need it to pinpoint the exact day, group, and state, not just the row number.
Solution found:
df.loc[(df['Date'] == '2021-01-03') & (df['Group'] == '002') & (df['State'] == 'AZ'), 'Sub'] = 3
Any help would be appreciated.
