這就是你想做的......

# load your data into a DataFrame

data="""StartTime EndTime

9:08 9:10

9:10 9:35

9:35 9:55

9:55 10:10

10:10 10:20

"""

from StringIO import StringIO # import from io for Python 3

df = pd.read_csv(StringIO(data), header=0, sep=' ', index_col=None)

# convert strings to Pandas Timestamps (we will ignore the date bit) ...

import datetime as dt

df.StartTime = [dt.datetime.strptime(x, '%H:%M') for x in df.StartTime]

df.EndTime = [dt.datetime.strptime(x, '%H:%M') for x in df.EndTime]

# assumption - all intervals are less than 60 minutes

# - ie. no multi-hour intervals

# add rows

dfa = df[df.StartTime.dt.hour != df.EndTime.dt.hour].copy()

dfa.EndTime = [dt.datetime.strptime(str(x), '%H') for x in dfa.EndTime.dt.hour]

# play with the start hour ...

df.StartTime = df.StartTime.where(df.StartTime.dt.hour == df.EndTime.dt.hour,

other = [dt.datetime.strptime(str(x), '%H') for x in df.EndTime.dt.hour])

# bring back together and sort

df = pd.concat([df, dfa], axis=0) #top/bottom

df = df.sort('StartTime')

# convert the Timestamps to times for easy reading

df.StartTime = [x.time() for x in df.StartTime]

df.EndTime = [x.time() for x in df.EndTime]

和收益

In [40]: df

Out[40]:

StartTime EndTime

0 09:08:00 09:10:00

1 09:10:00 09:35:00

2 09:35:00 09:55:00

3 09:55:00 10:00:00

3 10:00:00 10:10:00

4 10:10:00 10:20:00

總結

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