Pandas dataframe datetime to time then to seconds

Question

I have a dataframe. A column contains timestamps. I would like to remove dates and convert the time to seconds.

First I converted them to datetime:

In:
df_time = pd.to_datetime(df["Timestamp"])

Out:
0     2017-11-07 13:09:00
1     2017-11-07 13:11:00
2     2017-11-07 13:13:00
3     2017-11-07 13:15:00
dtype: datetime64[ns]

Then I removed dates:

In:
df_time = pd.Series([val.time() for val in df_time])

Out:
0      13:09:00
1      13:11:00
2      13:13:00
3      13:15:00
4      13:17:00
dtype: object

But they became objects and I did not managed to convert them to datetime-like objects to convert them into seconds. I know there are some similar threads I went trhough them.

I thank your help in advance.

Solution 1

Since you are converting it to datetime series, simply use basic maths to get the seconds i.e

df_time = pd.to_datetime(df["Timestamp"])

(df_time.dt.hour*60+df_time.dt.minute)*60 + df_time.dt.second

0    47340
1    47460
2    47580
3    47700
Name: Timestamp, dtype: int64

Solution 2

I think you need timedeltas by to_timedelta with times created by split and selecting second lists by str[1], then total_seconds and last cast to int:

df_time = pd.to_timedelta(df["Timestamp"].str.split().str[1]).dt.total_seconds().astype(int)
print (df_time)
0    47340
1    47460
2    47580
3    47700
Name: Timestamp, dtype: int32

Detail:

print (df["Timestamp"].str.split().str[1])
0    13:09:00
1    13:11:00
2    13:13:00
3    13:15:00
Name: Timestamp, dtype: object

print (pd.to_timedelta(df["Timestamp"].str.split().str[1]))
0   13:09:00
1   13:11:00
2   13:13:00
3   13:15:00
Name: Timestamp, dtype: timedelta64[ns]

---

Or if need seconds form datetimes use dt.second:

df_time = pd.to_datetime(df["Timestamp"]).dt.second
print (df_time)
0    0
1    0
2    0
3    0
Name: Timestamp, dtype: int64

Solution 3

if you are substracting for duration then use below to convert in seconds (tsession['EndTime'] -tsession['StartTime'])/ np.timedelta64(1, 's')