Generate multiple new DataFrames based on the datetime-CodePudding

I have a single DataFrame in the following format:

Date        Hour        Information
                               
2020-11-28  11:14:28           10.0
2020-11-28  11:14:30           15.4
2020-11-28  11:14:33            6.9
2020-11-28  11:14:35           27.0
2020-11-28  11:14:37           70.0
2020-11-28  11:14:40           37.1
2020-11-28  11:14:42            2.4
2020-11-28  11:15:20           11.9
2020-11-28  11:15:22           14.0
2020-11-28  11:15:24          122.8
2020-11-28  11:15:27          10.12
2020-11-28  11:15:29          56.86
2020-11-28  11:15:31          00.54
2020-11-28  11:15:34          01.87
2020-11-28  11:15:36            1.0
2020-11-28  11:24:21          45.45
2020-11-28  11:24:23            9.0
2020-11-28  11:24:26           90.5
2020-11-28  11:24:28            0.0
2020-11-28  11:24:30           5.34
.           .                     .
.           .                     .
.           .                     .
2020-11-30  10:34:12           10.0
2020-11-30  10:34:14           15.4

I need to be able to organize the information on the right column generating a new DataFrame containing the Information and the Hour for each datetime in the left column, so that i have like the following:

DataFrame1:
Datetime    Hour        Information
2020-11-28  11:14:28           10.0
2020-11-28  11:14:30           15.4
.           .                     .
.           .                     .
.           .                     .
2020-11-28  23:59:00           4.42

DataFrame2:
Datetime    Hour        Information
2020-11-29  00:00:00           18.7
.           .                     .
.           .                     .
.           .                     .
2020-11-28  23:59:00           7.54

And so on with all the other days I have, which not necessarily start in January 1st, but always has records for consecutive days. I've tried to use .groupby() but couldn't find a way to use it wihout getting the mean, sum, etc.

CodePudding user response：

If those multiple Dataframes that you want can be stored in tuple you could do the following

def format_df(df, date_time):
  df["DateTime"] = date_time
  return df.reset_index(drop=True)

dfs_array = tuple(format_df(grouped_df, date_time) for date_time, grouped_df in original_df.groupby("Date"))