Timedelta get months python

Calculate Date Using Python Timedelta Months

1. Python datetime Function
2. Use relativedelta() to Calculate Date Using Python

In this guide, we will learn the use of datetime in Python using the timedelta . We’ll see how we can calculate the date six months from the current date or any other date.

Python datetime Function

Well, first, we’ll look at how the datetime function works and what’s the drawback that limits the functionalities for us. The first thing that you need to know is to import the datetime in your code.

After that, you will create the instance of the datetime . Once you have created the instance, you can use its arithmetic functions.

You can subtract a day and a month. Take a look at the following code.

#instance of datetime date = datetime.datetime(2022,2,1) #subtracting 1 from the month date = date.replace(month=date.month-1) print(date) 

As you can see in the above code, with the help of an arithmetic function, we have subtracted a month from the date we set earlier. But here’s a catch, what if we try to subtract a month from the above result?

The code will give us an error. Take a look.

date = date.replace(month=date.month-1) 

 date = date.replace(month=date.month-1) ValueError: month must be in 1..12 

The datetime function doesn’t allow us to use arithmetic functions and subtract a whole year because it doesn’t support it. Similarly, if we were to add 1 or 2 while the current date lies in the last days of December, it would give out the same error.

# if you add 1 in date, it will throw an error because it doesn't support it date= datetime.datetime(2022,12,1) date_= date.replace(month=date_1.month+1) 

 date = date.replace(month=date.month+1) ValueError: month must be in 1..12 

So, coming back to the question, how can we calculate the date six months from the current date or any other date? The answer lies in using relativedelta .

Use relativedelta() to Calculate Date Using Python

Before we go ahead and use relativedelta in our Python code, we need to install dateutil to import the relativedelta from it. Run the following in your command prompt to install the dateutil .

pip install python-dateutil 

Once installed, you need to import the relativedelta from it.

from dateutil import relativedelta 

After that, we need to use both the datetime and relativedelta to solve the current problem. Take a look at the following code.

date = datetime.datetime(2022,1,1) # created the instance of the datetime and set the current date as 2022,1,1 

Now, we’ll create the instance of the relativedelta and set the month’s value as 1 .

r_date = relativedelta.relativedelta(months=1) 

Now, all we need to do is to subtract the instance of relativedelta from the instance of the datetime . It will give us our desired answer.

# if you subtract the relativedelta variable with the date instance, it will work correctly and change the year too. new_date = date - r_date print(new_date) 

Similarly, if we were to add 1 to the date, it would give us the desired output.

Now we can use this technique to calculate any date from the current date. That answers how we can calculate the date of six months from the current date.

Haider specializes in technical writing. He has a solid background in computer science that allows him to create engaging, original, and compelling technical tutorials. In his free time, he enjoys adding new skills to his repertoire and watching Netflix.

Related Article — Python Date

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Convert timedelta to Months in Python (2 Examples)

In this Python tutorial, you’ll learn how to convert a timedelta to months.

Example Data & Imported Libraries

First, we need to import the datetime module and the pandas library.

import datetime # importing datetime module import pandas as pd # importing pandas library

Next, let’s also construct some example data in Python:

dt1 = datetime.datetime(2017, 6, 5) # constructing sample datetime_1 print(dt1) # printing datetime_1 dt2 = datetime.datetime(2019, 8, 10) # constructing sample datetime_2 print(dt2) # printing datetime_2

Example 1: User-defined Function to Calculate Difference in Months

Our function basically gets the difference between the year and month attributes of the given datetime objects, then sums them up in terms of months.

def timedelta_in_months(end, start): # defining the function return 12 * (end.year - start.year) + (end.month - start.month) # returning the calculation

If we call the function and print the result, the following is obtained.

print(timedelta_in_months(dt2, dt1)) # printing the month difference # 26

Example 2: to_period() Function to Calculate Difference in Months

In this example, I’ll show how to calculate the difference by utilizing the to_period() function of the pandas library. For this example, we should convert the data to a pandas DataFrame as shown below.

df = pd.DataFrame("dt1" : [dt1], "dt2": [dt2]>) # constructing sample DataFrame print(df) # printing the DataFrame # dt1 dt2 #0 2017-06-05 2019-08-10

Now we can employ the to_period() function, which returns the date up to the time unit given by the parameter. In this case, it will return datetimes with the information of months and years only.

print(df["dt2"].dt.to_period('M'), df["dt1"].dt.to_period('M')) # printing to_period results # 2019-08, 2017-06

The advantage of the to_period() function is that it can calculate the datetime difference with respect to any time unit by a simple parameter change. For another use with a different parameter, see the tutorial Convert timedelta to Years in Python.

The calculation of the month difference can be seen below.

print(df["dt2"].dt.to_period('M').astype(int) - df["dt1"].dt.to_period('M').astype(int)) # printing the month difference # 26

Video, Further Resources & Summary

Do you need more explanations on the contents of this tutorial? Then you may want to have a look at the following video on the Statistics Globe YouTube channel. I explain the Python programming code of this page in the video:

The YouTube video will be added soon.

Furthermore, you might have a look at the other posts on www.statisticsglobe.com.

This article has illustrated how to calculate the time difference in months in Python. Please let me know in the comments section below, if you have further questions. Besides that, don’t forget to subscribe to my email newsletter to get updates on the newest articles.

This page was created in collaboration with Ömer Ekiz. Have a look at Ömer’s author page to get further details about his professional background, a list of all his tutorials, as well as an overview on his other tasks on Statistics Globe.

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Python get timedelta in months python code example

Let’s demonstrate a few ways to calculate the time delta in months in pandas. You can round the date to Month with and then subtract the result: Solution 2: you could also try: Solution 3: Update for pandas 1.3 If you want integers instead of objects: This works with pandas 1.1.1: The difference between two dates or times is represented as a timedelta object.

Pandas Timedelta in months

Update for pandas 0.24.0 :

Since 0.24.0 has changed the api to return MonthEnd object from period subtraction, you could do some manual calculation as follows to get the whole month difference:

12 * (df.today.dt.year - df.date.dt.year) + (df.today.dt.month - df.date.dt.month) # 0 2 # 1 1 # dtype: int64 

def month_diff(a, b): return 12 * (a.dt.year - b.dt.year) + (a.dt.month - b.dt.month) month_diff(df.today, df.date) # 0 2 # 1 1 # dtype: int64 

Prior to pandas 0.24.0. You can round the date to Month with to_period() and then subtract the result:

df['elapased_months'] = df.today.dt.to_period('M') - df.date.dt.to_period('M') df # date today elapased_months #0 2016-10-11 2016-12-02 2 #1 2016-11-01 2016-12-02 1 

df['months'] = (df['today'] - df['date']) / np.timedelta64(1, 'M') df # date today months #0 2016-10-11 2016-12-02 1.708454 #1 2016-11-01 2016-12-02 1.018501 

Update for pandas 1.3

If you want integers instead of MonthEnd objects:

df['elapsed_months'] = df.today.dt.to_period('M').view(dtype='int64') - df.date.dt.to_period('M').view(dtype='int64') df # Out[11]: # date today elapsed_months # 0 2016-10-11 2016-12-02 2 # 1 2016-11-01 2016-12-02 1 

This works with pandas 1.1.1:

df['elapsed_months'] = df.today.dt.to_period('M').astype(int) - df.date.dt.to_period('M').astype(int) df # Out[11]: # date today elapsed_months # 0 2016-10-11 2016-12-02 2 # 1 2016-11-01 2016-12-02 1 

Timedelta months in python Code Example, from datetime import timedelta from dateutil.relativedelta import relativedelta end_date = start_date + relativedelta(months=delta_period) + …

How to Calculate Timedelta in Months in Pandas

The difference between two dates or times is represented as a timedelta object. The duration describes the difference between two dates, datetime, or time occurrences, while the delta means an average of the difference. One may estimate the time in the future and past by using timedelta. This difference between two dates when calculated in terms of months, it’s called time delta in months. Let’s demonstrate a few ways to calculate the time delta in months in pandas.

Method 1: Calculate Timedelta Using pandas.Series.dt.to_period() function

Syntax:

Series.dt.to_period(*args, **kwargs)

converts datetime array to period array.

parameters :

freq= optional value, offset string or offset object

In this example, we read the time.csv and convert values in each column to DateTime. after converting columns to DateTime we use pandas.Series.dt.to_period() to calculate time delta in months. ‘M’ string in to_period() function symbolizes months. Month-end objects are returned.

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