I am trying to figure out a way to find the first and last time stamp for each asset within a dataframe for each day. For example, I have this data frame:

```
import pandas as pd
data = {
    'Date':['2022-01-01','2022-01-01','2022-01-01','2022-01-01','2022-01-01','2022-01-01',
           '2022-01-01' ,'2022-01-02','2022-01-02','2022-01-02','2022-01-02','2022-01-02','2022-01-02',
            '2022-01-02','2022-01-02','2022-01-03','2022-01-03','2022-01-03','2022-01-03','2022-01-03',
            '2022-01-03','2022-01-03','2022-01-03'],
    'Time':['12:01','12:05','14:07','11:01','13:06','17:12','15:15',
           '9:02','8:06','14:06','19:19','10:00','13:01','17:00','10:15',
           '8:00','9:00','7:15','16:04','15:02','17:10','12:06','15:00'],
    'Asset':[111,111,111,222,222,222,222,
             111,111,111,111,111,222,222,222,
            333,333,111,111,111,111,333,111]
}
df = pd.DataFrame(data)
df

```

Which looks like:

```
    Date    Time    Asset
0   2022-01-01  12:01   111
1   2022-01-01  12:05   111
2   2022-01-01  14:07   111
3   2022-01-01  11:01   222
4   2022-01-01  13:06   222
5   2022-01-01  17:12   222
6   2022-01-01  15:15   222
7   2022-01-02  9:02    111
8   2022-01-02  8:06    111
9   2022-01-02  14:06   111
10  2022-01-02  19:19   111
11  2022-01-02  10:00   111
12  2022-01-02  13:01   222
13  2022-01-02  17:00   222
14  2022-01-02  10:15   222
15  2022-01-03  8:00    333
16  2022-01-03  9:00    333
17  2022-01-03  7:15    111
18  2022-01-03  16:04   111
19  2022-01-03  15:02   111
20  2022-01-03  17:10   111
21  2022-01-03  12:06   333
22  2022-01-03  15:00   111

```

I would like to group this data by day and remove all duplicates for each asset in each day, only keeping the first and last timestamp for each value within each day. My ideal outcome would look like this:

```
data1 = {
    'Date':['2022-01-01','2022-01-01','2022-01-01','2022-01-01',
           '2022-01-02','2022-01-02','2022-01-02','2022-01-02',
           '2022-01-03','2022-01-03','2022-01-03','2022-01-03',],
    'Time':['12:01','14:07','11:01','17:12',
           '8:06','19:19','10:15','17:00',
           '8:00','12:06','7:15','17:10'],
    'Asset':[111,111,222,222,
            111,111,222,222,
            333,333,111,111]
}
df1 = pd.DataFrame(data1)
df1

```

Looking like:

```
Date    Time    Asset
0   2022-01-01  12:01   111
1   2022-01-01  14:07   111
2   2022-01-01  11:01   222
3   2022-01-01  17:12   222
4   2022-01-02  8:06    111
5   2022-01-02  19:19   111
6   2022-01-02  10:15   222
7   2022-01-02  17:00   222
8   2022-01-03  8:00    333
9   2022-01-03  12:06   333
10  2022-01-03  7:15    111
11  2022-01-03  17:10   111

```

Ideally, I would like to solve this problem in Python, however if there is an easier solution in R or SQL I am able to use those. Any help would be appreciated! Thanks in advance!