[FIXED] How to convert mins : secs into seconds in Python pandas data?

Issue

I am working on a football game dataset using python panda data. Now I have a column which is called 'gameClock', it has 'minutes : seconds' formation, like 7:52, 13:31, etc. I am trying to convert this format into seconds left for each quarter. For example, 7:52 means there is 7:08 time left for this quarter, it is equivalent to 428 seconds left for this quarter. But I have no idea how to convert these minutes:seconds time formation into all seconds left for the 900 seconds quarter. I tried the '.split()', but it returns an error like ''Series' object has no attribute 'split''. Please help me out with it. Thanks.

Solution

Convert to_timedelta, then get the total_seconds and rsub to 900:

df = pd.DataFrame({'gameClock': ['7:52', '13:31']})

df['out'] = (pd.to_timedelta('00:'+df['gameClock'])
             .dt.total_seconds().rsub(900)
             .convert_dtypes()
             )

Alternatively:

df['out'] = (pd.to_timedelta('00:'+df['gameClock'])
             .rsub(pd.Timedelta('900s'))
             .dt.total_seconds()
             .convert_dtypes()
             )

Output:

  gameClock  out
0      7:52  428
1     13:31   89

If you want to convert to seconds manually:

df['seconds'] = (df['gameClock']
                 .str.split(':', expand=True)
                 .astype(int)
                 .mul([60,1])
                 .sum(axis=1)
                 )

Output:

  gameClock  seconds
0      7:52      472
1     13:31      811

Answered By - mozway