得到下一个n个交易日的函数太慢了
我已经创建了一个函数，生成的下一个/前n个交易日，但对我的目的是太慢了。有谁能提出加快这个功能的方法吗?
def next_trading_day(start_day, num_trading_days, direction):
'''returns the next/previous trading day. Business_days determines how many days
back or into the future, direction determines whether back (-1) or forward (1)'''
for i in range(0, num_trading_days, direction):
next_day = start_day +datetime.timedelta(days=direction)
while next_day.weekday() in [5,6] or next_day not in mcal.get_calendar('NYSE').valid_days(start_date='2000-12-20', end_date='2020-01-10'):
next_day += datetime.timedelta(days=direction)
start_day = next_day
return start_day
我是这样使用这个函数的:
import pandas as pd
dict1 = [
{'date': '2016-11-27'},
{'date': '2016-11-28'},
{'date': '2016-11-27'},
]
df1= pd.DataFrame(dict1)
df1['date'] = pd.to_datetime(df1['date'])
df['Date-1']=df['date'].dt.date.apply(next_business_day, args=[-1,-1,])
问题来源StackOverflow 地址：/questions/59385992/get-next-n-trading-day-function-is-too-slow
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此检查next_day不在mcal.get_calendar('NYSE')中。valid_days(start_date='2000-12-20'， end_date='2020-01-10')非常耗时，因为它需要从7000天的数组中查找。你需要对每一个操作都这样做，所以我认为这是效率低下的主要原因。 您可以通过转换mcal.get_calendar('NYSE')来加快这种检查。valid_days(start_date='2000-12-20'， end_date='2020-01-10')设置，将查找从O(N)降低到O(log N)。 但我会选择另一种策略: 编辑:允许任意数量的滞后和领先
import pandas as pd import pandas_market_calendars as mcal def get_next_trading_day(df1, n): trading_days = pd.DataFrame({"date": mcal.get_calendar('NYSE').valid_days(start_date='2016-11-10', end_date='2016-12-01')}) trading_days['date'] = trading_days['date'].dt.tz_convert(None) trading_days = trading_days[~trading_days.date.dt.weekday.isin([5,6])] trading_days['next_trading_day'] = trading_days.date.shift(-n) # extract unique date from df1 df2 = pd.DataFrame({"date": pd.unique(df1['date'])}) # merge with the trading days data (non-trading day will have NA fields) df2 = df2.merge(trading_days, on='date', how='outer') # impute NA values df2.sort_values(by='date', inplace=True) df2['next_trading_day'].fillna(method= 'ffill' if n>0 else 'bfill', inplace=True) return df1.merge(df2, on='date', how='left') dict1 = [ {'date': '2016-11-27'}, {'date': '2016-11-28'}, {'date': '2016-11-27'}, ] df1= pd.DataFrame(dict1) df1['date'] = pd.to_datetime(df1['date']) print("Next trading day") print(get_next_trading_day(df1, 1)) print() print("Previous trading day") print(get_next_trading_day(df1, -1)) print() print("Next next trading day") print(get_next_trading_day(df1, 2)) print() print("Previous previous trading day") print(get_next_trading_day(df1, -2)) print()输出
Next trading day date next_trading_day 0 2016-11-27 2016-11-28 1 2016-11-28 2016-11-29 2 2016-11-27 2016-11-28 Previous trading day date next_trading_day 0 2016-11-27 2016-11-25 1 2016-11-28 2016-11-25 2 2016-11-27 2016-11-25 Next next trading day date next_trading_day 0 2016-11-27 2016-11-29 1 2016-11-28 2016-11-30 2 2016-11-27 2016-11-29 Previous previous trading day date next_trading_day 0 2016-11-27 2016-11-23 1 2016-11-28 2016-11-23 2 2016-11-27 2016-11-232019-12-25 22:10:21赞同 展开评论 打赏
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