Python is a very popular language because it is suitable for almost any type of data science task. And Pandas is one of the popular python-based data analysis toolkits and also provides pandas.bdate_range() function to return a fixed frequency DatetimeIndex. This function Returns a fixed frequency DatetimeIndex, with the business day(Mon to Fri) as the default frequency.
Syntax: pandas.bdate_range(start=None, end=None, periods=None, freq=’B’, tz=None, normalize=True, name=None, weekmask=None, holidays=None, closed=None, **kwargs)
Parameters :
start : string or datetime-like, default None.
end : string or datetime-like, default None.
periods : integer, default None.
freq : string or DateOffset, default ‘B’ (business daily).
tz : string or None.
normalize : bool, default False
name : str, default None
weekmask : str or None, default None
holidays : list-like or None, default None
Approach :
- Import the Pandas module
- Create a Parameter function that returns a boolean value
- Check the given date is returning boolean with pd.bdate_range() inside function
- Check if boolean is False then the date belongs to a weekday if boolean is true then is not weekday
Below is the implementation.
Python3
# importing Pandas module import pandas as pd # Creating a Function def check_weekday(date): # computing the parameter date # with len function res=len(pd.bdate_range(date,date)) if res == 0 : print("This is weekend") else: print("This is your working day") # user input date = "2020-08-17"check_weekday(date) date = "2020-08-16"check_weekday(date) |
Output :
This is your working day This is weekend
