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Understanding Business Day Offsets in pandas: pandas.tseries.offsets.BusinessDay.n


Data Offsets in pandas

pandas provides powerful tools for working with time series data. Data offsets are essential components that represent how you want to shift dates by specific units like days, weeks, months, or even custom business days. The pandas.tseries.offsets module offers various offset classes to achieve these time-based manipulations.

BusinessDay.n Offset

  • .n Parameter
    This parameter determines the number of business days you want to shift the date by.
    • Positive n moves the date forward by the specified number of business days, skipping weekends and holidays.
    • Negative n moves the date backward by the specified number of business days, again respecting weekends and holidays.
  • BusinessDay Class
    This class represents a business day offset. It considers weekends (Saturdays and Sundays) and holidays (which can be customized) as non-business days.

Example

import pandas as pd

# Create a pandas Timestamp
today = pd.Timestamp('2024-06-18')  # Tuesday

# Move forward 3 business days (skips Wednesday, Saturday, and Sunday)
three_business_days_later = today + pd.offsets.BusinessDay(n=3)
print(three_business_days_later)  # Output: 2024-06-21 (Friday)

# Move backward 2 business days (skips Monday and Friday)
two_business_days_earlier = today - pd.offsets.BusinessDay(n=2)
print(two_business_days_earlier)  # Output: 2024-06-14 (Friday)

Key Points

  • You can customize holidays using the holidays parameter in the BusinessDay constructor (not shown in the example above).
  • If the starting date falls on a weekend or holiday, it's adjusted to the nearest valid business day before applying the offset.
  • BusinessDay.n is useful for time series calculations that need to account for weekends and holidays.
  • For more advanced business day handling with custom weekday definitions or holidays, explore the CustomBusinessDay offset class.
  • pandas uses a default set of holidays for the United States. To specify custom holidays, refer to the pandas documentation for the holidays parameter.

Adding/Subtracting Business Days to a Pandas DatetimeIndex

import pandas as pd

# Create a pandas DatetimeIndex
dates = pd.date_range(start='2024-06-17', periods=5)  # Monday to Friday
print(dates)

# Add 2 business days to each date in the index
two_business_days_later = dates + pd.offsets.BusinessDay(n=2)
print(two_business_days_later)

# Subtract 1 business day from each date in the index
one_business_day_earlier = dates - pd.offsets.BusinessDay(n=1)
print(one_business_day_earlier)

This code creates a DatetimeIndex representing a week's worth of dates, then adds/subtracts business days to each date in the index, demonstrating the offset applied to multiple dates.

Finding the Next Business Day

import pandas as pd

# Create a pandas Timestamp on a Saturday
today = pd.Timestamp('2024-06-15')  # Saturday

# Find the next business day (Monday)
next_business_day = today + pd.offsets.BusinessDay(n=1)
print(next_business_day)

This code shows how to use BusinessDay.n to find the next business day from a non-business day.

Iterating Through Business Days Within a Date Range

import pandas as pd

from datetime import date

# Define start and end dates
start_date = date(2024, 6, 10)  # Monday
end_date = date(2024, 6, 20)  # Thursday

# Iterate through business days between start and end dates (excluding weekends)
current_date = start_date
while current_date <= end_date:
    if pd.is_business_day(current_date):
        print(current_date)
    current_date += pd.Timedelta(days=1)

This example iterates through a date range, checking for business days using pd.is_business_day and printing only those dates. It demonstrates using pd.Timedelta(days=1) to increment the date by one day in the loop.

  • Explore the holidays parameter in the BusinessDay constructor for custom holiday handling.
  • These are just a few examples. You can adapt BusinessDay.n to various scenarios involving business day calculations in pandas.

Other Business Day Offsets

  • Week: This offset represents a period of weeks. You can use it along with offset (number of weeks) and weekday (day of the week for the offset) parameters to achieve similar results as BusinessDay.n if you're primarily interested in week-based offsets, but it won't skip weekends.
  • CustomBusinessDay: This offset allows you to define custom business days based on your needs. You can specify a custom weekmask (e.g., include Saturdays as business days), provide a list of holidays to exclude, or integrate a specific business calendar.

Non-Business Day Offsets

  • Custom Offsets: You can create custom offsets using functions or classes to handle specific date shifting logic beyond built-in options.
  • DateOffset Subclasses: Pandas offers various offset classes like Day, MonthEnd, YearBegin, etc., which can be useful for non-business day-related date manipulations.

Choosing the Right Alternative

  • Have complex date shifting requirements
    Explore custom offsets.
  • Need simple non-business day offsets (days, months, years)
    Use appropriate DateOffset subclasses.
  • Want week-based offsets without weekend skipping
    Use Week.
  • Need custom business day definitions (weekmask, holidays)
    Use CustomBusinessDay.
  • Non-business day offsets like Day might not be ideal if you specifically need to account for weekends.
  • While CustomBusinessDay offers flexibility, it can be more complex to set up compared to BusinessDay.n if you only need basic business day handling.