What is the pandas.to_datetime() method?

Pandas is a Python library that is primarily used for data analysis. Dates are often provided in different formats and must be converted into single format DateTime objects before analysis. This is where pandas.to_datetime() comes in handy.

Let’s go over some of the most frequently used parameters that this function takes:

  • arg: an integer, float, string, list, or dict object to convert into a DateTime object.
  • dayfirst: set it to true if the input contains the day first.
  • yearfirst: set it to true if the input contains the year first.
  • utc: returns the UTC DatetimeIndex if True.
  • format: specifies the position of the day, month, and year in the date.

Code

Using pandas.to_datetime() with a date

import pandas as pd

# input in mm.dd.yyyy format

date = ['01.02.2019']

# output in yyyy-mm-dd format

print(pd.to_datetime(date))

Using pandas.to_datetime() with a date and time

import pandas as pd

# date (mm.dd.yyyy) and time (H:MM:SS)

date = ['01.02.2019 1:30:00 PM']

# output in yyyy-mm-dd HH:MM:SS

print(pd.to_datetime(date))

Using pandas.to_datetime() with dates in dd-mm-yyyy and yy-mm-dd format

import pandas as pd 

# pandas interprets this date to be in m-d-yyyy format

print(pd.to_datetime('8-2-2019'))

# if the specified date contains the day first, then 

# that has to be specified.

# output in yyyy-mm-dd format.

print(pd.to_datetime('8-2-2019', dayfirst = True))

# if the specified date contains the year first, then 

# that has to be specified.

# output in yyyy-mm-dd format.

print(pd.to_datetime('10-2-8', yearfirst = True))

Using pandas.to_datetime() to specify a format

import pandas as pd 

date = '2019-07-31 12:00:00-UTC'

print(pd.to_datetime(date, format = '%Y-%m-%d %H:%M:%S-%Z'))

Using pandas.to_datetime() to obtain a timezone-aware timestamp

import pandas as pd 

date = '2019-01-01T15:00:00+0100'

print(pd.to_datetime(date, utc = True))

Free Resources

Copyright ©2025 Educative, Inc. All rights reserved