使用另一个时间序列的索引重新采样时间序列 [英] Resample a time series with the index of another time series

问题描述

我有2个数据框，列相同但日期时间索引不同。我想重新取样其中一个，以使用另一个的索引，并从另一个索引中的任何日期使用前一个填充数据，其中没有数据。

I have 2 data frames with identical columns but different datetime indices. I want to resample one of them to use the index of the other and forward fill data from the one on any dates in the index of the other in which there wasn't data for.

import pandas as pd
import numpy as np
from datetime import datetime as dt

a_values = np.random.randn(4, 4)
a_index = [dt(2012, 3, 16), dt(2012, 3, 19), dt(2012, 3, 20), dt(2012, 3, 21)]
a = pd.DataFrame(data=a_values, index=a_index)

b_values = np.trunc(np.random.randn(3, 4) * 1000)
b_index = [dt(2012, 3, 16), dt(2012, 3, 19), dt(2012, 3, 21)]
b = pd.DataFrame(data=b_values, index=b_index)

c_insert = a.ix['2012-03-20']
c = b.append(c_insert).sort()
c.ix['2012-03-20'] = c.ix['2012-03-19']

'a'代表索引我的数据框喜欢用作重采样参考。 'b'表示我想重新采样和转发填充数据的数据帧。 'c'表示我希望看到的结果。

'a' represents the data frame whose index I'd like to use as the resampling reference. 'b' represents the data frame I'd like to resample and forward fill data. 'c' represents what I'd like the results to look like.

请注意'b'缺少'2012-03-20'中存在的'一个'。 'c'填充索引'2012-03-20'的列，其中'b'列中的数据为索引'2012-03-19'

Notice that 'b' is missing the '2012-03-20' index that exists in 'a'. 'c' populates the columns for index '2012-03-20' with the data in the columns from 'b' for index '2012-03-19'

pandas具有这样做的功能。

Does pandas have the functionality to do this.

提前致谢。

PiR

推荐答案

要通过参考索引重新采样，请使用 reindex 。

To resample by a reference index, use reindex.

In [11]: b.reindex(a.index, method='ffill')
Out[11]: 
               0     1     2     3
2012-03-16  -926  -625   736   457
2012-03-19 -1024   742   732 -1020
2012-03-20 -1024   742   732 -1020
2012-03-21  1090 -1163  1652   -94

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