How to compare SRT file timestamps in pandas?

I'm trying to compare Start_Time column and End_Time column that are in SRT timestamp format: 00:00:00,230

I used to_datetime to compare and created a new column to keep track of the difference between the end and start times. Check the answer for more info.

t1 = df['Start_Time']
t2 = df['End_Time']
diff = (t1-t2).astype('timedelta64[s]')  

df['Start_Time'] = pd.to_datetime(df['Start_Time'])
df['End_Time'] = pd.to_datetime(df['End_Time'])

But when I run the code above, it tells me this:

TypeError: Cannot convert input [1      00:00:00,230 ... end of list] Name: Start_Time, Length: 123, dtype: object] of type <class 'pandas.core.series.Series'> to Timestamp

Is there a way to compare the two columns while keeping the SRT formatting?

My end goal is this logic:

• while a row does not appear on the screen for at least 5s
• checkTime
• add text from the next row to current row AND replace current End_Time with next row End_Time
• delete next row
• checkTime again

PS:

1. Still not entirely sure how to add next row column value to current column value (so adding row 3 of Text column to row 2 of Text column with a space between them).
2. I think I can use loc to set current row at End_Time equal to the next row End_Time to replace the end timestamp but correct me if I'm wrong.

I used pd.to_datetime instead of pd.Timestamp and created a new column Difference in the dataframe to know the difference between end and start time.

I also kept a copy of the dataframe dfSRTTime before using to_datetime so I can keep the original formatting and will be working on editing both for the rest of my code. This will allow me to accurately check for the 5s difference while maintaining original SRT format when I export the file at the end.