Pandas - Convert HH:MM:SS.F string to seconds - Caveat : HH sometimes goes over 24H - date

Question

I have the following dataframe :
**flashtalking_df =**
+--------------+--------------------------+------------------------+
| Placement ID | Average Interaction Time | Total Interaction Time |
+--------------+--------------------------+------------------------+
| 2041083 | 00:01:04.12182 | 24:29:27.500 |
| 2041083 | 00:00:54.75043 | 52:31:48.89108 |
+--------------+--------------------------+------------------------+
where 00:01:04.12182 = HH:MM:SS.F
I need to convert both columns, Average Interaction Time, and Total Interaction Time into seconds.
The problem is that Total Interaction Time goes over 24h.
I found the following code which works for the most part. However, when the Total Interaction Time goes over 24h, it gives me
ValueError: time data '24:29:27.500' does not match format '%H:%M:%S.%f'
This is the function I am currently using, which I grabbed from another Stack Overflow question, for both Average Interaction Time and Total Interaction Time:
flashtalking_df['time'] = flashtalking_df['Total Interaction Time'].apply(lambda x: datetime.datetime.strptime(x,'%H:%M:%S.%f'))
flashtalking_df['timedelta'] = flashtalking_df['time'] - datetime.datetime.strptime('00:00:00.00000','%H:%M:%S.%f')
flashtalking_df['Total Interaction Time'] = flashtalking_df['timedelta'].apply(lambda x: x / np.timedelta64(1, 's'))
If there's an easier way, please let me know.
Thank you for all your help

Answer 1

I think you need first convert to_timedelta and then to seconds by astype:
df['Average Interaction Time'] = pd.to_timedelta(df['Average Interaction Time'])
.astype('timedelta64[s]')
.astype(int)
df['Total Interaction Time'] = pd.to_timedelta(df['Total Interaction Time'])
.astype('timedelta64[s]')
.astype(int)
.map('{:,.2f}'.format)
print (df)
Placement ID Average Interaction Time Total Interaction Time
0 2041083 64 88,167.00
1 2041083 54 189,108.00
Solution with total_seconds, thank you NickilMaveli:
df['Average Interaction Time'] = pd.to_timedelta(df['Average Interaction Time'])
.dt.total_seconds()
.map('{:,.2f}'.format)
df['Total Interaction Time'] = pd.to_timedelta(df['Total Interaction Time'])
.dt.total_seconds()
.map('{:,.2f}'.format)
print (df)
Placement ID Average Interaction Time Total Interaction Time
0 2041083 64.12 88,167.50
1 2041083 54.75 189,108.89