convert all objects present in timestamps otherwise ignore those columns

Basically I want to ignore objects that are not convertible to timestamps and convert the object timestamp columns into timestamps.

utc timestamps specifically.

data = {'timestamp_1': ['36:00.0', '46:44.0', '20:59.0', '57:27.0', '51:18.0'],
        'r1': [-1, 6, 10, 0, 0],
        'timestamp': ['18-06-2020 09:36:00', 
                      '19-06-2020  09:36:00',
                      '20-06-2020 09:36:00',
                      '21-06-2020 09:36:00',
                      '22-06-2020 09:36:00']
       }

data = pd.DataFrame(data = data)
data

>Solution :

If you want to explicitly try to convert all columns as if they were UTC timestamps:

for col in df:
    df[col] = pd.to_datetime(df[col], format='%d-%m-%Y %H:%M', errors='ignore')

print(df)

Output:

   time_tz rpd           timestamp
0  36:00.0  -1 2020-06-18 09:36:00
1  46:44.0   6 2020-06-19 09:36:00
2  20:59.0  10 2020-06-20 09:36:00
3  57:27.0   0 2020-06-21 09:36:00
4  51:18.0   0 2020-06-22 09:36:00

Better would probably be only converting the specific column:

df.timestamp = pd.to_datetime(df.timestamp) 
# Or, if some values may be invalid: pd.to_datetime(df.timestamp, errors='coerce')