我有两个日期时间索引 - 一个是工作日date_range
,另一个是假期列表。
我按开始日期和结束日期过滤假日列表。但现在我需要加入他们并删除任何重复项(假期和交易日都存在)。
最后,我需要将日期范围转换为格式化字符串列表,即:yyyy_mm_dd
我可以稍后迭代。
到目前为止,这是我的代码:
import datetime
import pandas as pd
from pandas.tseries.holiday import AbstractHolidayCalendar, Holiday, nearest_workday, \
USMartinLutherKingJr, USPresidentsDay, GoodFriday, USMemorialDay, \
USLaborDay, USThanksgivingDay
class USTradingCalendar(AbstractHolidayCalendar):
rules = [
Holiday('NewYearsDay', month=1, day=1, observance=nearest_workday),
USMartinLutherKingJr,
USPresidentsDay,
GoodFriday,
USMemorialDay,
Holiday('USIndependenceDay', month=7, day=4, observance=nearest_workday),
USLaborDay,
USThanksgivingDay,
Holiday('Christmas', month=12, day=25, observance=nearest_workday)
]
def get_trading_close_holidays(year):
inst = USTradingCalendar()
return inst.holidays(datetime.datetime(year-1, 12, 31),
datetime.datetime(year, 12, 31))
start_date = "2017_07_01"
end_date = "2017_08_31"
start_date = datetime.datetime.strptime(start_date,"%Y_%m_%d").date()
end_date = datetime.datetime.strptime(end_date,"%Y_%m_%d").date()
date_range = pd.bdate_range(start = start_date, end = end_date, name =
"trading_days")
holidays = get_trading_close_holidays(start_date.year)
holidays = holidays.where((holidays.date > start_date) &
(holidays.date < end_date))
holidays = holidays.dropna(how = 'any')
date_range = date_range.where(~(date_range.trading_days.isin(holidays)))
答案 0 :(得分:0)
考虑按布尔条件过滤:
date_range = date_range[date_range.date != holidays.date]
print(date_range) # ONE HOLIDAY 2017-07-04 DOES NOT APPEAR
# DatetimeIndex(['2017-07-03', '2017-07-05', '2017-07-06', '2017-07-07',
# '2017-07-10', '2017-07-11', '2017-07-12', '2017-07-13',
# '2017-07-14', '2017-07-17', '2017-07-18', '2017-07-19',
# '2017-07-20', '2017-07-21', '2017-07-24', '2017-07-25',
# '2017-07-26', '2017-07-27', '2017-07-28', '2017-07-31',
# '2017-08-01', '2017-08-02', '2017-08-03', '2017-08-04',
# '2017-08-07', '2017-08-08', '2017-08-09', '2017-08-10',
# '2017-08-11', '2017-08-14', '2017-08-15', '2017-08-16',
# '2017-08-17', '2017-08-18', '2017-08-21', '2017-08-22',
# '2017-08-23', '2017-08-24', '2017-08-25', '2017-08-28',
# '2017-08-29', '2017-08-30', '2017-08-31'],
# dtype='datetime64[ns]', name='trading_days', freq=None)
使用astype()
将日期时间索引转换为字符串类型数组,甚至tostring()
进行列表转换:
strdates = date_range.date.astype('str').tolist()
print(strdates)
# ['2017-07-03', '2017-07-05', '2017-07-06', '2017-07-07', '2017-07-10',
# '2017-07-11', '2017-07-12', '2017-07-13', '2017-07-14', '2017-07-17',
# '2017-07-18', '2017-07-19', '2017-07-20', '2017-07-21', '2017-07-24',
# '2017-07-25', '2017-07-26', '2017-07-27', '2017-07-28', '2017-07-31',
# '2017-08-01', '2017-08-02', '2017-08-03', '2017-08-04', '2017-08-07',
# '2017-08-08', '2017-08-09', '2017-08-10', '2017-08-11', '2017-08-14',
# '2017-08-15', '2017-08-16', '2017-08-17', '2017-08-18', '2017-08-21',
# '2017-08-22', '2017-08-23', '2017-08-24', '2017-08-25', '2017-08-28',
# '2017-08-29', '2017-08-30', '2017-08-31']