CODEWITHSUNDEEP
pythonpandas
Neil
Neil

Reputation: 8247

How to subtract time when there is a date change in pandas?

I have following dataframe in pandas

    start_date        start_time        end_time
    2018-01-01        23:55:00          00:05:00
    2018-01-02        00:05:00          00:10:00
    2018-01-03        23:59:00          00:05:00

I want to calculate the time difference. But, for 1st and 3rd observation, there is a date change in end_time.

How can I do it in pandas?

Currently, I am using the logic where end_time is less than start_time I am creating one more column called end_date where it increments the start_date by 1 and then subtracts the time.

Is there any other way to do it?

Upvotes: 1

Views: 96

Answers (1)

jezrael
jezrael

Reputation: 863801

Solution working with timedeltas - if difference are days equal -1 then add one day:

df['start_time'] = pd.to_timedelta(df['start_time'])
df['end_time'] = pd.to_timedelta(df['end_time'])

d =  df['end_time'] - df['start_time']
df['diff'] = d.mask(d.dt.days == -1, d + pd.Timedelta(1, unit='d'))
print (df)
   start_date start_time end_time     diff
0  2018-01-01   23:55:00 00:05:00 00:10:00
1  2018-01-02   00:05:00 00:10:00 00:05:00
2  2018-01-03   23:59:00 00:05:00 00:06:00

Another solution:

s = df['end_time'] - df['start_time']
df['diff'] = np.where(df['end_time'] < df['start_time'], 
                      s + pd.Timedelta(1, unit='d'), 
                      s)
print (df)

   start_date start_time end_time     diff
0  2018-01-01   23:55:00 00:05:00 00:10:00
1  2018-01-02   00:05:00 00:10:00 00:05:00
2  2018-01-03   23:59:00 00:05:00 00:06:00

Upvotes: 2

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