A Complete Guide to Python DateTime Functions

In this tutorial, we will cover python datetime module and how it is used to handle date, time and datetime formatted columns (variables). It includes various practical examples which would help you to gain confidence in dealing dates and times with python functions. In general, Date types columns are not easy to manipulate as it comes with a lot of challenges like dealing with leap years, different number of days in a month, different date and time formats or if date values are stored in string (character) format etc.
Table of Contents

Introduction : datetime module

It is a python module which provides several functions for dealing with dates and time. It has four classes as follows which are explained in the latter part of this article how these classes work.
  1. datetime
  2. date
  3. time
  4. timedelta
datetime python with examples

People who have no experience of working with real-world datasets might have not encountered date columns. They might be under impression that working with dates is rarely used and not so important. To enlighten them, I have listed down real-world examples wherein using datetime module can be beneficial.

  1. Selecting all the saving account holders who were active on 30th June, 2018 and checking their status whether they are still active
  2. Identifying insureds who filed more than 20 claims in the last 3 months
  3. Identifying customers who made multiple transactions in the last 6 months
  4. Extracting dates from timestamp values
Import datetime module
You can import or load datetime module by using the command below -
import datetime
You don't need to install this module as it comes bundled with the installation of python software.


Here we are using datetime.date class which is used to represent calendar date values. today() method is used to fetch current date.

datetime.date(2019, 7, 19)
In order to display it like a proper calendar date, we can wrap it within print( ) command.


Create Date object

date class follows the syntax as shown below-
date(year, month, day)
dt = datetime.date(2019, 10, 20)



Extract day, month and year from date values




Customize Date Formats

You can customize the format of dates by defining the date formats using strftime method. It converts date objects to strings.
%d refers to day of the month. In 20-10-2019, %d returns 20.
%m refers to month of the year. In 20-10-2019, %m returns 10.
%Y refers to year. The letter 'Y' is in upper case. In 20-10-2019, %Y returns 2019.
%y refers to year in two-digit format. In 20-10-2019, %y returns 19.

Other popular format codes
  • %a returns the first three letter of the weekday Sun
  • %A returns the complete name of the weekday Sunday
  • %b returns the first three letters of the month Oct
  • %B returns the complete name of the month October

dt.strftime("%b %d, %Y")
Oct 20, 2019

dt.strftime("%B %d, %Y")
October 20, 2019

dt.strftime("%a %B %d, %Y")
Sun October 20, 2019

dt.strftime("%A %B %d, %Y")
Sunday October 20, 2019

dt.strftime("%A, %B %d, %Y")
Sunday, October 20, 2019


Time values are defined with datetime.time class. It follows the syntax as shown below -
datetime.time(hour, minute, second, microseconds)
t = datetime.time(21, 2, 3)

How to get hour, minute and seconds from time values





How to convert time to AM PM format

  • %I converts 24 hour time format to 12 hour format.
  • %p returns AM PM based on time values.
  • %H returns hours of the time value.
  • %M returns minutes of the time value.
  • %S returns seconds of the time value.
t.strftime("%I:%M %p")
09:02 PM

Handle both dates and time

datetime library has another class named datetime.datetime class which is used to represent date plus time. You can call it timestamp. now() or today() method of datetime class is used to extract current date and time.
dt = datetime.datetime.now()

2019-07-20 17:05:05.699416
%c represents locale date and time. %X represents locale time.
Sat Jul 20 17:05:05 2019

dt.strftime("%A %B %d %X")
Saturday July 20 17:05:05

dt.strftime("%A %B %d %H:%M")
Saturday July 20 17:05

Create datetime object

The syntax of datetime class is as follows-
datetime(year, month, day, hour, minute, second, microsecond)
dt = datetime.datetime(2019, 7, 20, 10, 51, 0)
2019-07-20 10:51:00

dt.strftime('%d-%m-%Y %H-%M')
20-07-2019 10-51

How to convert a string to datetime in python?

from dateutil.parser import parse
print(parse('March 01, 2019'))

2019-03-01 00:00:00

How to get current time?

We can use the same function we used in the previous section and extract time from the returned value using time() method.

How to get current day of the week?

Suppose you want to extract the day number. 1 for Monday and 7 for Sunday. In the example below it returns 6 as it's Saturday on 20th July, 2019.

Calculate future or past dates

With the use of timedelta, you can add or subtract days, weeks, hours, minutes, seconds, microseconds and milliseconds. It is very useful when you want to calculate future or past dates. Suppose you are asked to identify all the customers who enrolled to product in the last 30 days. To solve this, you need to compute the date which is 30 days before the today's date.
#30 days ahead
delta = datetime.timedelta(days=30)
print(dt + delta)
2019-08-19 10:51:00

#30 days back
print(dt - delta)
2019-06-20 10:51:00

delta = datetime.timedelta(days= 10, hours=3, minutes=30, seconds=30)
print(dt + delta)
2019-07-30 14:21:30

delta = datetime.timedelta(weeks= 4, hours=3, minutes=30, seconds=30)
print(dt + delta)
2019-08-17 14:21:30
In timedelta, months and years options are missing which means you cannot calculate future dates increment by month(s) or year(s). To accomplish this task, we can use dateutil package. Let's import this package by submitting the code below -
from dateutil.relativedelta import *
If it's not installed on your system, install it by running this command pip install python-dateutil
#1 Month ahead
print(dt + relativedelta(months=+1))
2019-08-20 10:51:00

#1 Month Back
print(dt + relativedelta(months=-1))
If you are wondering how this relativedelta(months=+1) is different from datetime.timedelta(days=30), observe the returned values (result) of both the commands.
Since July has 31 days, 30 days ahead using this datetime.timedelta(days=30) returns 2019-08-19 10:51:00. relativedelta(months=+1) returns 2019-08-20 10:51:00 which is a complete 1 month.
#Next month, plus one week
print(dt + relativedelta(months=+1, weeks=+1))

#Next Year
print(dt + relativedelta(years=+1))
Consider Leap Years
relativedelta method from dateutil package takes care of leap year while calculating future or past dates. Year 2000 was a leap year so there were 29 days in the February month. But next year has only 28 days in February.
print(datetime.date(2000, 2, 29)+ relativedelta(years=+1))


Difference between Two Dates

Suppose you need to calculate the number of days between two dates. It is a very common data problem statement when you need to calculate the tenure of customers given the information - when they opened their account(start date) and when the accounts got closed (end date).
date1 = datetime.date(2020, 10, 25)
date2 = datetime.date(2019, 12, 25)
diff = date1- date2

How would you calculate the number of months between two dates?
One way is to calculate number of days and then divide it by 30 to get number of months. But it is not always correct as some months have 31 days.
Not full-proof Solution
Correct Solution
date1.month - date2.month + 12*(date1.year - date2.year)
How it works?
  • date1.month - date2.month returns -2
  • 12*(date1.year - date2.year) returns 12
  • -2 + 12 = 10
Important Point
Suppose you want to calculate the number of months between 31/10/2018 and 01/11/2018, the above suggested method will return 1 as two dates lie in a month difference. You may find it incorrect as number of days in between two dates is 1. Do you know INTCK function (with default setting) in SAS software also returns 1? What's the usage of returning 1? It is useful when you need to sort time series data into bins. For example, daily data can be accumulated to monthly data to process as a monthly series. If you expect 0 as number of months, you can use the code shown above under "Not full-proof Solution".

How to work with dates on pandas dataframe?

In real-world, we generally import data from external files and store it in pandas DataFrame. Hence it is important to understand how we perform date and time operations on DataFrame. Let's create a sample dataframe for illustration purpose.
df=pd.DataFrame({"A":["2019-01-01", "2019-05-03", "2019-07-03"],
                 "B":["2019-03-02", "2019-08-01", "2019-10-01"] })
Let's check the column types.
Here both columns A and B are strings (character values).
A    object
B    object
dtype: object
It is required to convert the columns to datetime object since these variables are stored in string.
df['A'] = pd.to_datetime(df['A'])
df['B'] = pd.to_datetime(df['B'])

A    datetime64[ns]
B    datetime64[ns]
dtype: object
In order to calculate the number of days using columns A and B on pandas dataframe, you just need to take a difference of these two columns.
df['C'] = df['B'] - df['A']

          A          B       C
0 2019-01-01 2019-03-02 60 days
1 2019-05-03 2019-08-01 90 days
2 2019-07-03 2019-10-01 90 days
The column C we have computed is in datetime format. In order to get the difference value in integer format, you can submit the command below. dt enables pandas to use datetime methods.
df['C'] = (df['B'] - df['A']).dt.days

          A          B   C
0 2019-01-01 2019-03-02  60
1 2019-05-03 2019-08-01  90
2 2019-07-03 2019-10-01  90
Get 3 months past date
The pure pythonic way is to define function in lambda and it runs on all the rows.
from dateutil.relativedelta import *
df['D'] = df["B"].apply(lambda x: x - relativedelta(months=3))

           A          B   C          D
0 2019-01-01 2019-03-02  60 2018-12-02
1 2019-05-03 2019-08-01  90 2019-05-01
2 2019-07-03 2019-10-01  90 2019-07-01
Another way is to use built-in function DateOffset of pandas package which adds or subtracts days, months, years, weeks, hours, minutes, seconds, microseconds and nanoseconds.
df['D1'] = df['B'] - pd.DateOffset(months=3)
Filtering dataframe by date

Suppose you want to select only those rows where column B has values greater than 1st May, 2019.

Select Data between two dates

Suppose you want to select rows from pandas dataframe between two dates (let's say between 1st May and 30th September).

df[df.B.between(datetime.datetime(2019,5,1), datetime.datetime(2019,9,30))]

df[(df['B'] > datetime.datetime(2019,5,1)) & (df['B'] < datetime.datetime(2019,9,30))]

How to work with different timezones

Manytimes we have date values in different time zones and we need to convert it to our local timezone. It is not easy to solve this manually. In python, there is a library called pytz for setting and conversion of timezone.

You can find all the timezones by submitting this command.
import pytz
To set datetime object in a particular timezone (let's say Asia/Kolkata), you can use the parameter called tzinfo for this.
dt = datetime.datetime(2019, 7, 20, 10, 10, 0, tzinfo=pytz.timezone('Asia/Kolkata'))
To convert it to US/Arizona timezone, we can use the method called astimezone for conversion. If you would observe the date has been changed after conversion as difference between these two timezones is more than 12 hours.

2019-07-19 21:17:00-07:00
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About Author:

Deepanshu founded ListenData with a simple objective - Make analytics easy to understand and follow. He has over 10 years of experience in data science. During his tenure, he has worked with global clients in various domains like Banking, Insurance, Private Equity, Telecom and Human Resource.

19 Responses to "A Complete Guide to Python DateTime Functions"
  1. Very comprehensive. Will be useful in my astrology project. Dasha calculations. Cheers

  2. Nice Article with good explanation.

  3. Hi Deepanshu,

    Thanks for sharing such a wonderful learning material.

    One thing would like to know I'm using Jupitor notebook and tried your time zone code over there and unable to get the expected output you mentioned above.

    Used the same code you mentioned above in timezones section.

    Please help me to get the desired output.

    NIKHIl Jain

    1. You need to wrap it in print( ) function. I have updated the code in the article. Please check and confirm the same. THanks!

    2. Yup it's working thanks Deepanshu..😊

  4. date1.month - date2.month + 12*(date1.year - date2.year)

    Isn't this formula wrong.

    Difference between 25/01/2019 and 05/02/2019 is not 1 month (in terms of months)

    1. I have added explanation in the post to clarify this point.

  5. Thanks. It is very helpful. Please let me know the code in python if I want to find the lost customers who hasn’t order in a three month increment past 6 months?

  6. Great article! How do you filter a dataframe so you can it only has monthly values or weekly values - within a specified range?

  7. Nice article , but how to select date in range ?

  8. How to write a function in python which identifies all columns containing dates?

  9. Nice work... Can you please address for this time format: '2010-224T12:66:56.855Z' in series

  10. Thanks for sharing this information as I am new to Python. I need your help in resolving the following issue: Reading data from excel sheet with column having '2021-02-01 16:24:00'. I have created two additional columns in the dataframe using the following construct:

    df['StConnDate'] = pd.to_datetime(df['StartTimeCon']).dt.date
    df['StConnTime'] = pd.to_datetime(df['StartTimeCon']).dt.time

    The column StConnDate contains the correct value but column StConnTime contains 16:23:59.999999 instead of 16:24:00 How do i overcome this issue.

    Thanks in advance for your help.

  11. how to convert MAY-15 object type to datetime 2015-May


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