Issue
I want to create a new column if survey_start date is with 12 months prior to start_date then 1 else 0
| ID | survey_date | start_date |
|---|---|---|
| 1 | 2019-05-01 | 2022-05-01 |
| 1 | 2021-05-01 | 2022-05-01 |
| 1 | 2023-05-01 | 2022-05-01 |
| 1 | 2021-12-01 | 2022-05-01 |
| 2 | 2010-01-01 | 2010-02-01 |
| 2 | 2011-05-01 | 2010-02-01 |
output
| ID | survey_date | start_date | new_column |
|---|---|---|---|
| 1 | 2019-05-01 | 2022-05-01 | 0 |
| 1 | 2021-05-01 | 2022-05-01 | 1 |
| 1 | 2023-05-01 | 2022-05-01 | 0 |
| 1 | 2021-12-01 | 2022-05-01 | 1 |
| 2 | 2010-01-01 | 2010-02-01 | 1 |
| 2 | 2011-05-01 | 2010-02-01 | 0 |
How do I do this in pandas dataframe?
Solution
here is one way to do it using np.where
df['new_col'] = np.where(((df['start_date'].astype('datetime64') - df['survey_date'].astype('datetime64') ).dt.days).between(0,366),1, 0)
df
ID survey_date start_date new_col
0 1 2019-05-01 2022-05-01 0
1 1 2021-05-01 2022-05-01 1
2 1 2023-05-01 2022-05-01 0
3 1 2021-12-01 2022-05-01 1
4 2 2010-01-01 2010-02-01 1
5 2 2011-05-01 2010-02-01 0
Answered By – Naveed
Answer Checked By – Jay B. (AngularFixing Admin)