Python Program to Get total Business days between two dates

Given two dates, our task is to write a Python program to get total business days, i.e weekdays between the two dates.

Example:

Input : test_date1, test_date2 = datetime(2015, 6, 3), datetime(2015, 7, 1)

Output : 20

Explanation : Total weekdays, i.e business days are 20 in span.

Input : test_date1, test_date2 = datetime(2015, 6, 3), datetime(2016, 7, 1)

Output : 282

Explanation : Total weekdays, i.e business days are 282 in span.

Method 1: Using timedelta() + sum() + weekday()

In this, all the dates are extracted using timedelta(), by incrementing differences till the end date. Post that, business days are filtered using weekday(), summing all which has a value less than 5. i.e Mon – Fri.

Python3

# Python3 code to demonstrate working of
# Business days in range
# Using timedelta() + sum() + weekday()
from datetime import datetime, timedelta

# initializing dates ranges
test_date1, test_date2 = datetime(2015, 6, 3), datetime(2015, 7, 1)

# printing dates
print("The original range : " + str(test_date1) + " " + str(test_date2))

# generating dates
dates = (test_date1 + timedelta(idx + 1)
         for idx in range((test_date2 - test_date1).days))

# summing all weekdays
res = sum(1 for day in dates if day.weekday() < 5)

# printing
print("Total business days in range : " + str(res))

Output:

The original range : 2015-06-03 00:00:00 2015-07-01 00:00:00
Total business days in range : 20

Time complexity : O(n)

Space Complexity : O(1)

Method #2 : Using np.busday_count()

This is inbuilt function that can be used to directly employ to solve this task.

Python3

# Python3 code to demonstrate working of
# Business days in range
# Using np.busday_count
from datetime import datetime, timedelta
import numpy as np

# initializing dates ranges
test_date1, test_date2 = datetime(2015, 6, 3), datetime(2015, 7, 1)

# printing dates
print("The original range : " + str(test_date1) + " " + str(test_date2))

# generating total days using busday_count()
res = np.busday_count(test_date1.strftime('%Y-%m-%d'),
                      test_date2.strftime('%Y-%m-%d'))

# printing
print("Total business days in range : " + str(res))

Output:

The original range : 2015-06-03 00:00:00 2015-07-01 00:00:00
Total business days in range : 20

Time complexity : O(1)

Space Complexity : O(1)

Method #3 : Using pandas.bdate_range()

This is another inbuilt function that can be used to directly employ to solve this task. Returns total business dates list inclusive of the start and end date. 

Python3

# Python3 code to demonstrate working of
# Business days in range
# Using pd.bdate_range
from datetime import datetime
import pandas as pd

# initializing dates ranges
test_date1, test_date2 = datetime(2015, 6, 3), datetime(2015, 6, 30)

# printing dates
print("The original range : " + str(test_date1) + " " + str(test_date2))

# generating total days using pd.bdate_range()
# len() gets the number of days
# includes both last and first date.
res = len(pd.bdate_range(test_date1.strftime('%Y-%m-%d'),
                         test_date2.strftime('%Y-%m-%d')))

# printing result
print("Total business days in range : " + str(res))

Output : 

The original range : 2015-06-03 00:00:00 2015-06-30 00:00:00
Total business days in range : 20

Time complexity : O(n)

Space Complexity : O(n)

Method #4: Using a loop and weekday() function

1. First, the program initializes two variables start_date and end_date as datetime objects with the date values of June 3, 2015 and June 30, 2015 respectively.
2. Then, it initializes a variable num_business_days to 0 to keep count of the number of business days.
3. Next, the program enters a while loop with the condition that the current_date is less than or equal to the end_date. The loop continues until it reaches the last date in the range.
4. Inside the loop, the program checks if the current_date is a weekday (Monday to Friday) using the weekday() method. The method returns an integer representing the day of the week, where 0 is Monday and 6 is Sunday. If the weekday() value is less than 5, which represents a weekday, then the program increments the num_business_days variable by 1.
5. The program then increments the current_date by one day using the timedelta function from the datetime module.
6. The loop continues to iterate through each day in the date range until it reaches the end_date.
7. Finally, the program prints the total number of business days between the two dates by displaying the value of num_business_days.

Python3

from datetime import datetime, timedelta

# initializing dates ranges
start_date, end_date = datetime(2015, 6, 3), datetime(2015, 6, 30)

# initializing business days count
num_business_days = 0

# looping through each day in the date range
current_date = start_date
while current_date <= end_date:
    # checking if the current day is a weekday
    if current_date.weekday() < 5:
        num_business_days += 1
    # incrementing the current day by one day
    current_date += timedelta(days=1)

# printing the result
print("Total business days in range:", num_business_days)

Output

Total business days in range: 20

Time complexity: O(n), where n is the number of days in the date range.

Auxiliary space: O(1), as we only need to keep track of one variable.

Method #5: Using numpy:

 Algorithm:

1. Initialize the start_date and end_date.
2. Create a numpy array of dates using np.arange() function, which includes all the dates between the start_date and end_date.
3. Convert the numpy array of dates to weekday numbers using np.datetime_as_string() and .astype() functions.
4. Calculate the number of weekdays in the numpy array using np.count_nonzero() function.
5. Print the total number of business days in the date range.

Python3

import numpy as np
from datetime import datetime, timedelta

# initializing dates ranges
start_date, end_date = datetime(2015, 6, 3), datetime(2015, 6, 30)

# creating an array of dates between the start and end dates
dates = np.arange(start_date, end_date + timedelta(days=1), dtype='datetime64[D]')

# getting the weekday number for each date in the array
weekday_num = np.datetime_as_string(dates, unit='D').astype('datetime64[D]').view('int') % 7

# counting the number of weekdays in the array
num_business_days = np.count_nonzero((weekday_num < 5))

# printing the result
print("Total business days in range:", num_business_days)
#This code is contributed by vinay Pinjala.

Output:
Total business days in range: 20

Time complexity:

The np.arange() function takes O(1) time complexity.
The np.datetime_as_string() function takes O(n) time complexity, where n is the number of dates in the numpy array.
The .astype() function takes O(n) time complexity.
The np.count_nonzero() function takes O(n) time complexity.
Therefore, the overall time complexity of this algorithm is O(n).

Space complexity:

The np.arange() function creates a numpy array with a size of (end_date – start_date) + 1, which takes O(n) space complexity, where n is the number of dates in the numpy array.
The np.datetime_as_string() function creates a new numpy array of the same size, which takes O(n) space complexity.
The .astype() function creates a new numpy array of the same size, which takes O(n) space complexity.
The np.count_nonzero() function does not create any new array, so it takes O(1) space complexity.
Therefore, the overall space complexity of this algorithm is O(n).