【初心者向け】Pandasのis_month_startでカスタムビジネス月の月初を判定：詳細ガイド

pandas.tseries.offsets.CustomBusinessMonthEnd.is_month_start は、カスタムビジネス月のオフセットが指定された日付が月の初日かどうかを判定する関数です。

用途

この関数は、以下の様な場面で役立ちます。

• カスタムビジネス月の期間を計算したい場合
• 月の初日を基準としたデータ分析を行いたい場合
• 特定の月の初日に処理を実行したい場合

引数

• tsTimestamp: 判定対象の日付

戻り値

• False: 指定された日付が月の初日ではない場合
• True: 指定された日付が月の初日の場合

例

import pandas as pd

# カスタムビジネス月オフセットを作成
offset = pd.tseries.offsets.CustomBusinessMonthEnd(n=2)  # 2ヶ月前の月の末日

# 判定対象の日付
date = pd.Timestamp('2024-07-15')

# 判定結果
is_month_start = offset.is_month_start(date)
print(is_month_start)  # True

上記の例では、2024-07-15 が2ヶ月前の月の末日であるため、True と判定されます。

• Pandas のバージョンによって、引数や戻り値の仕様が異なる場合があります。最新の情報は公式ドキュメントを参照してください。
• is_month_start 関数は、オフセットの種類に関わらず使用できます。
• CustomBusinessMonthEnd オフセットは、祝日と週末を除いたビジネスデーを基準に月をカウントします。

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Identifying the first business day of the current month

import pandas as pd

today = pd.Timestamp('today')
current_month_offset = pd.offsets.CustomBusinessMonthEnd(n=0)

first_business_day_of_current_month = today + current_month_offset

is_first_business_day_month_start = current_month_offset.is_month_start(first_business_day_of_current_month)
print(is_first_business_day_month_start)  # True

Checking if a specific date is the first business day of the following month

import pandas as pd

target_date = pd.Timestamp('2024-08-05')
current_month_offset = pd.offsets.CustomBusinessMonthEnd(n=0)

is_target_date_first_business_day_of_next_month = current_month_offset.is_month_start(target_date)
print(is_target_date_first_business_day_of_next_month)  # True

Identifying all first business days of a specific year

import pandas as pd

year = 2023
start_date = pd.Timestamp(f'{year}-01-01')
end_date = pd.Timestamp(f'{year}-12-31')

monthly_offset = pd.offsets.CustomBusinessMonthEnd(n=1)
first_business_days = []

current_date = start_date
while current_date <= end_date:
    if monthly_offset.is_month_start(current_date):
        first_business_days.append(current_date)
    current_date += monthly_offset

print(first_business_days)

import pandas as pd

today = pd.Timestamp('today')
current_month_offset = pd.offsets.CustomBusinessMonthEnd(n=0)
next_month_offset = pd.offsets.CustomBusinessMonthEnd(n=1)

first_business_day_of_current_month = today + current_month_offset
first_business_day_of_next_month = today + next_month_offset

business_days_between = first_business_day_of_next_month - first_business_day_of_current_month
print(business_days_between.days)  # Number of business days between the two dates

---

Using pd.Timestamp.is_month_start and CustomBusinessDay offset

import pandas as pd

def is_first_business_day_of_month(date):
    # Check if the date is the first day of the month
    is_month_start = date.is_month_start

    if is_month_start:
        # Convert the date to a timestamp
        timestamp = pd.Timestamp(date)

        # Create a CustomBusinessDay offset with the specified date as the starting point
        custom_business_day_offset = pd.offsets.CustomBusinessDay(n=0, reference=timestamp)

        # Calculate the next business day
        next_business_day = timestamp + custom_business_day_offset

        # Check if the next business day is the same as the original date
        is_first_business_day = next_business_day == timestamp
        return is_first_business_day

    else:
        return False

date = pd.Timestamp('2024-07-15')
is_first_business_day = is_first_business_day_of_month(date)
print(is_first_business_day)  # True

This approach utilizes the pd.Timestamp.is_month_start method to determine if the date is the first day of the month. If it is, a CustomBusinessDay offset is created with the reference set to the date. The next business day is calculated using the offset, and if it matches the original date, it confirms that the date is the first business day of the month.

Combining pd.DateOffset and conditional checks

import pandas as pd

def is_first_business_day_of_month(date):
    # Convert the date to a timestamp
    timestamp = pd.Timestamp(date)

    # Calculate the first day of the current month
    first_day_of_month = timestamp.replace(day=1)

    # Check if the first day of the month is a weekend
    is_weekend = first_day_of_month.weekday() in [5, 6]

    if is_weekend:
        # If the first day is a weekend, calculate the next business day
        next_business_day = first_day_of_month + pd.DateOffset(days=1)
        is_first_business_day = next_business_day == date
    else:
        # If the first day is not a weekend, check if it's the same as the input date
        is_first_business_day = first_day_of_month == date

    return is_first_business_day

date = pd.Timestamp('2024-07-15')
is_first_business_day = is_first_business_day_of_month(date)
print(is_first_business_day)  # True

This method involves calculating the first day of the current month using timestamp.replace(day=1). Then, it checks if the first day falls on a weekend (weekday() returns 5 for Saturdays and 6 for Sundays). If it's a weekend, the next business day is calculated using pd.DateOffset(days=1) and compared to the original date. Otherwise, it directly compares the first day of the month to the input date.

• Benchmarking the performance of different approaches might be necessary if the code is used for large-scale date processing.
• It's important to ensure that the CustomBusinessDay offset is configured with appropriate holiday and weekend rules if exact business day calculations are crucial.
• The choice of method depends on the specific context and performance requirements. The CustomBusinessMonthEnd offset provides a more direct approach, while the other methods offer more flexibility and control over the date manipulation process.