Python pandas 自定义商务日

Question

我试图在 pandas 中过滤一些时间序列数据，但没有任何运气。非常感谢任何关于我做错的提示。首先，我试图只过滤 7 月份的数据2013 然后再次过滤数据以获取数据集样本的每小时平均值。

最终我想做的是使用 CustomBusinessDay 函数过滤工作日或周一、周二、周三等个别工作日的数据，如上所述。

我被 CustomBusinessDay 的代码注释掉了

import pandas as pd
import numpy as np
from pandas.tseries.offsets import CustomBusinessDay


time = pd.date_range('6/28/2013', periods=2000, freq='45min')
data = pd.Series(np.random.randint(100, size=2000), index=time)

print(data)

##weekmask = 'Mon Tue Wed Thu Fri'


df = data.truncate(before='7/1/2013', after='7/31/2013')
df = df.groupby(df.index.hour).mean()
print(df)

##df = CustomBusinessDay(weekmask=weekmask)
##df = pd.bdate_range(start=None, end=None, periods=None, freq='B')
##
##print(df)

Answer 1

Ultimately what I am wanting to do is filter the data as described above in addition for Weekdays, OR individual weekdays Mondays, Tuesdays, Wednesday, etc. with the CustomBusinessDay function.

您是否考虑过使用 DatetimeIndex.dayofweek？

The day of the week with Monday=0, Sunday=6

# Exclude Sundays
data.loc[data.index.dayofweek != 6]

# Weekends only
data.loc[data.index.dayofweek.isin([5, 6])]

# Weekdays only
data.loc[~data.index.dayofweek.isin([5, 6])]

此外，我认为 df = df.groupby(df.index.hour).mean() 的替代方法是：

df.resample('H').mean()

Python pandas 自定义商务日

Python pandas CustomBusinessDay

python

python-3.x

pandas

data-science