Try Series.diff()
:
import pandas as pd
import io
txt = """0 2013-12-19 09:03:21.223000
1 2013-12-19 11:34:23.037000
2 2013-12-19 11:34:23.050000
3 2013-12-19 11:34:23.067000
4 2013-12-19 11:34:23.067000
5 2013-12-19 11:34:23.067000
6 2013-12-19 11:34:23.067000
7 2013-12-19 11:34:23.067000
8 2013-12-19 11:34:23.067000
9 2013-12-19 11:34:23.080000
10 2013-12-19 11:34:23.080000
11 2013-12-19 11:34:23.080000
12 2013-12-19 11:34:23.080000
13 2013-12-19 11:34:23.080000
14 2013-12-19 11:34:23.080000
15 2013-12-19 11:34:23.097000
16 2013-12-19 11:34:23.097000
17 2013-12-19 11:34:23.097000
18 2013-12-19 11:34:23.097000
19 2013-12-19 11:34:23.097000
"""
s = pd.read_csv(io.BytesIO(txt), delim_whitespace=True, parse_dates=[[1,2]], header=None, index_col=1, squeeze=True)
s.diff()
result:
0 NaT
1 02:31:01.814000
2 00:00:00.013000
3 00:00:00.017000
4 00:00:00
5 00:00:00
6 00:00:00
7 00:00:00
8 00:00:00
9 00:00:00.013000
10 00:00:00
11 00:00:00
12 00:00:00
13 00:00:00
14 00:00:00
15 00:00:00.017000
16 00:00:00
17 00:00:00
18 00:00:00
19 00:00:00
Name: 1_2, dtype: timedelta64[ns]