How to add a column with the current date in pandas?

Follow this tutorial to add a date and time column into a pandas DataFrame.

Step 1: Acquire your data

You most probably have already a pandas DataFrame. However if not, here’s some data that you can use for this example:

import pandas as pd

# create two columns
dates = pd.Series(pd.date_range(start='6/1/23', periods=5,freq='B'))
interviews = [185, 138, 137, 192, 137]

# construct DataFrame
dates = pd.Series(pd.date_range(start='6/1/23', periods=5,freq='B'))
interviews = [185, 138, 137, 192, 137]

Step 2: Get the current datetime Timestamp as a column

You can easily get the current data and time Timestamp as a DataFrame column. THe following code adds as column named today_ts to our DataFrame:

today_ts =
campaign['today_ts'] = today_ts

Alternatively, you can use the assign DataFrame method:

campaign = campaign.assign(today_ts = today_ts)

Step 3: Add a date column to your DataFrame

If you are interested to add just the date itself (without the time value) you can use the dt accessor for the relevant Series / Column:

campaign['today_date'] = pd.to_datetime(campaign['today_ts']

Here’s our DataFrame:

02023-06-011852023-05-21 17:28:59.7670522023-05-21
12023-06-021382023-05-21 17:28:59.7670522023-05-21
22023-06-051372023-05-21 17:28:59.7670522023-05-21
32023-06-061922023-05-21 17:28:59.7670522023-05-21
42023-06-071372023-05-21 17:28:59.7670522023-05-21

Step 4: Perform time calculations

Now that our data is complete we can easily perform some calculations, for example, subtracting times.

As an example, we can create a new column storing the calculated time difference between two days as following:

campaign['delta'] = campaign['dates'] - campaign['today_date']

This will render the following data:

02023-06-011852023-05-21 17:28:59.7670522023-05-2111 days
12023-06-021382023-05-21 17:28:59.7670522023-05-2112 days
22023-06-051372023-05-21 17:28:59.7670522023-05-2115 days
32023-06-061922023-05-21 17:28:59.7670522023-05-2116 days
42023-06-071372023-05-21 17:28:59.7670522023-05-2117 days

How to subtract dates and times in Python?

Here are a few related cases that i encounter in my daily work with Data:

  1. Difference between two dates
  2. Difference between a date and a timedelta object.
  3. Subtracting other timedeltas from date objects : years, months, hours, minutes, seconds.

Subtract days from a datetime object in Python

Let’s define two date objects that represents the hire and quitting date of a random employee.

import datetime
hire_date =,4, 7)
quit_date =,4, 24)

Then let’s calculate the overall time worked:

print("The overall time that this employee worked in our company was:" + str(quit_date - hire_date).split(',')[0]+".")

Here’s the result:

The overall time that this employee worked in our company was:382 days.

Subtract timedeltas from datetimes

We’ll now define a datetime and timedelta representing the hire date and the number of days on the job for our fictitious employee:

import datetime
hire_date =,4, 7)
worked_days = datetime.timedelta(282)

Let’s quickly calculate the quitting date of this employee:

print("The hire date of this employee worked in our company was: " + str(quit_date - worked_days)+".")

Here’s the result:

The hire date of this employee worked in our company was: 2021-06-08.

Note: Another way to accomplish this would have been using the dateutil.relativedelta method

print(quit_date - relativedelta(days = 282))

Subtract years from datetime

The dateutil.relativedelta utility allows to very easily subtract time from a date object.

from dateutil.relativedelta import relativedelta
graduation_date = quit_date - relativedelta(years = 2)

print("His graduation date was on: " + str(graduation_date))

The result will be:

His graduation date was on: 2020-04-24

Note: Don’t forget to import the utility into your Python program as otherwise you will receive the following NameError:

NameError: name 'relativedelta' is not defined

Subtract months from a Python date

As we just learnt, we can use the relativedelta utility to calculate time differences relative to a Python daytime / timestamp.

The following code helps to subtract 24 months from a datetime:

from dateutil.relativedelta import relativedelta
graduation_date = quit_date - relativedelta(months = 24)

print("His graduation date was on: " + str(graduation_date))

Find time differences in hours, minutes and seconds

In a similar fashion we can subtract any time units from our datetime:

  • Seconds: graduation_date = quit_date – relativedelta(seconds=500000)
  • Minutes:quit_date – relativedelta(minutes=45255)


How to add a column containing date ranges in pandas DataFrame?

Use the following code to create a column containing a rand of dates starting today:

import datetime
today_date =
campaign['date_range_col'] = pd.date_range(start = today_date, periods = len(campaign), freq = 'D')

Can i insert a column containing specific dates into a DataFrame?

Assuming that you have a Python list containing dates, that has the same length of your DataFrame, you can assign it as a new column:

campaign= campaign.assing(dates_col = pd.Series(dates_list))