Working days
Contents
I’ve worked a lot with Excel spreadsheets on financial data. Among other things, I had to use working days. Excel provides a function (WORKDAY
) to compute working days but holidays have to be provided manually and in France we have a lot of public holidays :-)—and they are not all anchored.
The python Pandas package comes from the financial analysis domain and in consequence, it provides a lot of features to manipulate time series data.
Here is how to create a custom calendar. With this french example you should be able to create your own.
from pandas.tseries.holiday import AbstractHolidayCalendar, Holiday, EasterMonday, Easter
from pandas.tseries.offsets import Day, CustomBusinessDay
class FrBusinessCalendar(AbstractHolidayCalendar):
""" Custom Holiday calendar for France based on
https://en.wikipedia.org/wiki/Public_holidays_in_France
- 1 January: New Year's Day
- Moveable: Easter Monday
(Monday after Easter Sunday (one day after Easter Sunday)
- 1 May: Labour Day
- 8 May: Victory in Europe Day
- Moveable Ascension Day
(Thursday, 39 days after Easter Sunday)
- 14 July: Bastille Day
- 15 August: Assumption of Mary to Heaven
- 1 November: All Saints' Day
- 11 November: Armistice Day
- 25 December: Christmas Day
"""
rules = [
Holiday('New Years Day', month=1, day=1),
EasterMonday,
Holiday('Labour Day', month=5, day=1),
Holiday('Victory in Europe Day', month=5, day=8),
Holiday('Ascension Day', month=1, day=1, offset=[Easter(), Day(39)]),
Holiday('Bastille Day', month=7, day=14),
Holiday('Assumption of Mary to Heaven', month=8, day=15),
Holiday('All Saints Day', month=11, day=1),
Holiday('Armistice Day', month=11, day=11),
Holiday('Christmas Day', month=12, day=25)
]
Here is how to get the public holidays whatever the year.
import pandas as pd
from datetime import date
# Creating some boundaries
year = 2016
start = date(year, 1, 1)
end = start + pd.offsets.MonthEnd(12)
# Creating a custom calendar
cal = FrBusinessCalendar()
# Getting the holidays (off-days) between two dates
cal.holidays(start=start, end=end)
# DatetimeIndex(['2016-01-01', '2016-03-28', '2016-05-01', '2016-05-05',
# '2016-05-08', '2016-07-14', '2016-08-15', '2016-11-01',
# '2016-11-11', '2016-12-25'],
# dtype='datetime64[ns]', freq=None)
And finally this is how to count the number of working days by month — it is very useful for a lot of things like building a rough schedule.
from pandas.tseries.offsets import CDay
# Creating a series of dates between the boundaries
# by using the custom calendar
se = pd.bdate_range(start=start,
end=end,
freq=CDay(calendar=cal)).to_series()
# Counting the number of working days by month
se.groupby(se.dt.month).count().head()
# 1 20
# 2 21
# 3 22
# 4 21
# 5 21