Calculate Timedelta using months in integer
In the previous method, Monthends object is returned. If we want it to be in integer we have to convert it using the astype() function or by using view(dtype=’int64′).
Python3
# import packages and librariesimport pandas as pdimport seaborn as snsimport matplotlib.pyplot as plt# reading the csv filedata = pd.read_csv('time.csv')# converting columns to datetimedata['start_date'] = pd.to_datetime(data['start_date'])data['end_date'] = pd.to_datetime(data['end_date'])# calculating time delta in monthsdata['time_delta_months'] = data['end_date'].dt.to_period('M').astype(int) - \ data['start_date'].dt.to_period('M').astype(int)# print(data)print(data) |
Output:
Example 2: Using .view(dtype=’int64′) to convert into integers
Python3
# import packages and librariesimport pandas as pdimport seaborn as snsimport matplotlib.pyplot as plt# reading the csv filedata = pd.read_csv('time.csv')# converting columns to datetimedata['start_date'] = pd.to_datetime(data['start_date'])data['end_date'] = pd.to_datetime(data['end_date'])# calculating time delta in monthsdata['time_delta_months'] = data['end_date'].dt.to_period('M').view(dtype='int64') -\ data['start_date'].dt.to_period('M').view(dtype='int64')# print(data)print(data) |
Output:
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.
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