Alternatives to CustomBusinessMonthBegin.is_year_end for pandas Data Offsets

Functionality

• This specific method checks whether a given timestamp (ts) coincides with the end of a year (December 31st) according to the CustomBusinessMonthBegin offset definition.
• The is_year_end method is part of the CustomBusinessMonthBegin class in pandas, which represents a date offset that falls on the business day closest to the beginning of a month.

Data Offsets in pandas

• The is_year_end method is a utility function within this offset class that helps determine if a particular date aligns with the end of a year when using the CustomBusinessMonthBegin offset.
• The CustomBusinessMonthBegin offset allows you to perform date-related operations by considering only business days (excluding weekends and holidays, if specified). It aligns dates to the beginning of a month based on business days.
• Data offsets in pandas are specialized objects used to manipulate and navigate dates within pandas DataFrames and Series.

Return Value

• is_year_end returns a boolean value:
  • True if the provided timestamp (ts) falls on the end of a year (December 31st) relative to the CustomBusinessMonthBegin offset.
  • False if ts doesn't correspond to the end of a year.

Example

import pandas as pd

# Create a datetime object
dt = pd.to_datetime('2023-12-31')

# Create a CustomBusinessMonthBegin offset (default is first business day of month)
offset = pd.offsets.CustomBusinessMonthBegin()

# Check if 'dt' is the end of the year according to the offset
is_year_end = offset.is_year_end(dt)

print(is_year_end)  # Output: True (because December 31st is the end of 2023)

• If you don't need to consider business days, you can use the simpler YearEnd offset for checking year ends.
• CustomBusinessMonthBegin.is_year_end is specifically designed for the CustomBusinessMonthBegin offset and might not directly apply to other offset types.

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Example 1: Checking Non-Year-End Date

import pandas as pd

# Create a datetime object not at year end
dt = pd.to_datetime('2024-06-15')  # Today's date (assuming June 16, 2024)

# Create a CustomBusinessMonthBegin offset
offset = pd.offsets.CustomBusinessMonthBegin()

# Check if 'dt' is the end of the year according to the offset
is_year_end = offset.is_year_end(dt)

print(is_year_end)  # Output: False (because June 15th is not December 31st)

• This example demonstrates how a custom weekmask can affect the is_year_end result.

import pandas import as pd

# Create a CustomBusinessMonthBegin offset with a custom weekmask (Wednesday and Thursday)
offset = pd.offsets.CustomBusinessMonthBegin(weekmask="Wed Thu")

# Create a datetime object at year end (considering Wednesday/Thursday weekmask)
dt = pd.to_datetime('2023-12-28')  # Wednesday in the last week of 2023 (assuming Wednesday weekmask)

# Check if 'dt' is the end of the year according to the offset
is_year_end = offset.is_year_end(dt)

print(is_year_end)  # Output: True (because December 28th is the last Wednesday of 2023)

• If December 28th (a Wednesday) falls within the last business week of December according to the weekmask, is_year_end will return True.
• The weekmask parameter allows you to specify which weekdays are considered business days for the offset. In this case, only Wednesday and Thursday are business days.

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pandas.tseries.offsets.YearEnd

• Use the YearEnd offset if you don't require considering business days:

import pandas as pd

# Create a datetime object
dt = pd.to_datetime('2023-12-31')

# Create a YearEnd offset
offset = pd.offsets.YearEnd()

# Check if 'dt' is the end of the year
is_year_end = offset.is_anchored(dt)  # Use is_anchored for YearEnd

print(is_year_end)  # Output: True

Conditional Statement and month Attribute

• Utilize a conditional statement along with the month attribute of the datetime object:

import pandas as pd

dt = pd.to_datetime('2024-06-15')

is_year_end = dt.month == 12

print(is_year_end)  # Output: False (June is not December)

dt.isoformat().endswith('-12-31')

• This approach is less efficient but works in simpler cases:

import pandas as pd

dt = pd.to_datetime('2023-12-31')

is_year_end = dt.isoformat().endswith('-12-31')

print(is_year_end)  # Output: True

Choosing the Right Alternative

The best alternative depends on your specific use case:

• Avoid dt.isoformat().endswith for performance-critical code due to string manipulation.
• If you need more flexibility within conditional statements, use the month attribute.
• If business days are irrelevant, use YearEnd.