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Pandas: How to Calculate a Difference Between Two Times

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You can use the following syntax to calculate a difference between two times in a pandas DataFrame:

#calculate time difference in hours
df['hours_diff'] = (df.end_time - df.start_time) / pd.Timedelta(hours=1)

#calculate time difference in minutes
df['min_diff'] = (df.end_time - df.start_time) / pd.Timedelta(minutes=1)

#calculate time difference in seconds
df['sec_diff'] = (df.end_time - df.start_time) / pd.Timedelta(seconds=1)

This particular example calculates the difference between the times in the end_time and start_time columns of some pandas DataFrame.

The following example shows how to use this syntax in practice.

Example: Calculate Difference Between Two Times in Pandas

Suppose we have the following pandas DataFrame:

import pandas as pd

#create DataFrame
df=pd.DataFrame({'start_time':pd.date_range(start='5/25/2020',periods=6,freq='15min'),
                 'end_time':pd.date_range(start='5/26/2020',periods=6,freq='30min')})

#view DataFrame
print(df)

           start_time            end_time
0 2020-05-25 00:00:00 2020-05-26 00:00:00
1 2020-05-25 00:15:00 2020-05-26 00:30:00
2 2020-05-25 00:30:00 2020-05-26 01:00:00
3 2020-05-25 00:45:00 2020-05-26 01:30:00
4 2020-05-25 01:00:00 2020-05-26 02:00:00
5 2020-05-25 01:15:00 2020-05-26 02:30:00

We can use the following syntax to calculate the time difference between the start_time and end_time columns in terms of hours, minutes, and seconds:

#calculate time difference in hours
df['hours_diff'] = (df.end_time - df.start_time) / pd.Timedelta(hours=1)

#calculate time difference in minutes
df['min_diff'] = (df.end_time - df.start_time) / pd.Timedelta(minutes=1)

#calculate time difference in seconds
df['sec_diff'] = (df.end_time - df.start_time) / pd.Timedelta(seconds=1)

#view updated DataFrame
print(df)

           start_time            end_time  hours_diff  min_diff  sec_diff
0 2020-05-25 00:00:00 2020-05-26 00:00:00       24.00    1440.0   86400.0
1 2020-05-25 00:15:00 2020-05-26 00:30:00       24.25    1455.0   87300.0
2 2020-05-25 00:30:00 2020-05-26 01:00:00       24.50    1470.0   88200.0
3 2020-05-25 00:45:00 2020-05-26 01:30:00       24.75    1485.0   89100.0
4 2020-05-25 01:00:00 2020-05-26 02:00:00       25.00    1500.0   90000.0
5 2020-05-25 01:15:00 2020-05-26 02:30:00       25.25    1515.0   90900.0

The new columns contain the time differences between the start_time and end_time columns in various units.

For example, consider the first row:

  • The difference between the start time and end time is 24 hours.
  • The difference between the start time and end time is 1,440 minutes.
  • The difference between the start time and end time is 86,400 seconds.

Note that in this example, the start_time and end_time columns are already formatted as datetimes.

If your time columns are instead currently formatted as strings, you can use pd.to_datetime to first convert each column to a datetime format before calculating the difference between the times:

#convert columns to datetime format
df[['start_time', 'end_time']] = df[['start_time', 'end_time]].apply(pd.to_datetime)

You can then proceed to calculate the time differences between the columns since they are both now in a datetime format that pandas can recognize.

Additional Resources

The following tutorials explain how to perform other common operations in pandas:

How to Create a Date Range in Pandas
How to Extract Month from Date in Pandas
How to Convert Timestamp to Datetime in Pandas

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