How to calculate day max for time series along with relevant hour?

Question

I have a dataframe with some timeseries inside. It has 3 columns: day, hour and value:

day	hour	value
12-Jan	11-00	14
12-Jan	12-00	100
12-Jan	13-00	345
12-Jan	14-00	195
13-Jan	12-00	76
13-Jan	13-00	221
13-Jan	14-00	102
13-Jan	15-00	395

As you see max value for 12 Jan is observed at 13-00.

I want to calculate max of the "value" for each "day". I can do it via simple

df.groupby("day")["value"].max()

It works, but after grouping apparently we have hour information erased. The question is: how can I build dataFrame which would contain day max value along with the hour when that value was observed , ie

day	hour when maxValue was observed	maxValue
12-Jan	13-00	345
13-Jan	15-00	395

?

Answer 1

EDIT

I created a sample of your df :

         day   hour  value
0 2021-01-12  11-00     14
1 2021-01-12  12-00    100
2 2021-01-12  13-00    345
3 2021-01-12  14-00    195
4 2021-01-13  12-00     76
5 2021-01-13  13-00    221
6 2021-01-13  14-00    102
7 2021-01-13  15-00    395

And run this code on it:

res = pd.merge(df.groupby('day').agg({'value':'max'},as_index=False).add_prefix('max_'),df,how='left',left_on='max_value',right_on='value')

And got back:

   max_value        day   hour  value
0        345 2021-01-12  13-00    345
1        395 2021-01-13  15-00    395