Timing calculation from int variables in Python Pandas

Question

I have date data in int format with following this insturction: Change date format to int in Python Pandas

Let's assume that that there are 2 different columns : 'Timestamp_start' and 'Timestamp_End'. As the timestamp value is converted in int, how can calculate the time differences between two timestamps in 'minutes' unit?

For example, if the value is formatted in yyyymmddhhss, Timestamp_start is 201911030903 and Timestamp_End is 201911031006. The result might be '63' minutes.

As there are complicated datetime conversions in Python Pandas, I am lost how to calculate the time differences in minutes. The result will be int as well.

Nicolas Gervais · Accepted Answer · 2019-11-24 16:58:12Z

0

You can use pd.to_datetime for this.

import pandas as pd

ts1 = '201911030903'
ts2 = '201911031006'

sr = pd.Series([ts1, ts2])

sr = pd.to_datetime(sr)

That was just to make a reproducible problem. This gives:

Out[44]: 
0   2019-11-03 09:03:00
1   2019-11-03 10:06:00
dtype: datetime64[ns]

Now onto your problem, just subtract and divide by 60 (seconds):

diff = sr[1] - sr[0]

int(diff.seconds/60)

Out[41]: 63

answered Nov 24, 2019 at 16:58

Nicolas Gervais

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