| volume | price | datetime |
|---|---|---|
| 400 | 9 | 2021-09-29 04:00:00-04:00 |
| 900 | 22 | 2021-09-29 06:00:00-04:00 |
| 1000 | 31 | 2021-09-29 08:00:00-04:00 |
| 400 | 21 | 2021-09-29 10:00:00-04:00 |
| 1200 | 31 | 2021-09-29 12:00:00-04:00 |
I'd like to find the datetime where the highest price ($31) is.
If the highest price appears twice, return the earlier datetime.
Expected output should be 2021-09-29 08:00:00-04:00.
CodePudding user response：
I think you're looking for pandas.Series.idxmax():
row = df.loc[df['price'].idxmax()]
Output:
>>> row
volume 1000
price 31
datetime 2021-09-29 08:00:00-07:00
Name: 2, dtype: object