本文介绍了工作时间以外的掩码时间序列的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着跟版网的小编来一起学习吧！
问题描述
您好，如果时间序列索引在工作时间之外，我想屏蔽一个每小时时间序列.
Hello I have an hourly timeseries that I would like to mask if the timeseries index is outside business hours.
我可以实现我想要的工作日数据，但不能实现每小时数据
I can achieve what I want for business day data but not hourly data
import datetime
import pandas as pd
import numpy as np
from pandas.tseries.offsets import *
st = datetime.datetime(2013, 1, 1)
ed = datetime.datetime(2013, 2, 1)
myrange = pd.date_range(st, ed, freq='H')
ts = pd.Series(np.random.randn(len(myrange)), index=myrange)
ts.asfreq(BDay()).asfreq(Day())
我尝试生成 BDay 日期范围，然后将频率更改为每小时，但这不起作用.
I have tried generating a BDay date range and then changing the freq to hourly but this doesn't work.
newrange = pd.date_range(datetime.datetime(2013, 1, 1), datetime.datetime(2013, 1, 1), freq='B')
#but adding this doesn't work .asfreq(Hour())
ts[ts.index.isin(newrange)].asfreq(Hour()) #Of course this only gives one value on the day
谢谢
推荐答案
将您的时间限制为您可以使用的工作日:
To restrict your times to Business days you could use:
ts = ts.ix[ts.index.map(BDay())]
和indexer_between_time 限制营业时间:
and indexer_between_time to restrict between business hours:
ts = ts.ix[ts.index.indexer_between_time(time(7), time(18))]
限制在工作时间内的工作日(以任一顺序应用这些).
To restrict to Business days within business hours (apply these in either order).
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