概述

这适用于玩具示例,但不适用于我的数据(详见下文).

例：

import pandas as pd
import numpy as np

df1 = pd.DataFrame(np.random.randn(6,4),columns=['A','B','C','D'],index=pd.date_range('1/1/2011',periods=6,freq='D'))
df1

A   B   C   D
2011-01-01  -0.487926   0.439190    0.194810    0.333896
2011-01-02  1.708024    0.237587    -0.958100   1.418285
2011-01-03  -1.228805   1.266068    -1.755050   -1.476395
2011-01-04  -0.554705   1.342504    0.245934    0.955521
2011-01-05  -0.351260   -0.798270   0.820535    -0.597322
2011-01-06  0.132924    0.501027    -1.139487   1.107873

s1 = pd.Series(np.random.randn(3),name='foo',periods=3,freq='2D'))
s1

2011-01-01   -1.660578
2011-01-03   -0.209688
2011-01-05    0.546146
Freq: 2D,Name: foo,dtype: float64

pd.concat([df1,s1],axis=1)

A   B   C   D   foo
2011-01-01  -0.487926   0.439190    0.194810    0.333896    -1.660578
2011-01-02  1.708024    0.237587    -0.958100   1.418285    NaN
2011-01-03  -1.228805   1.266068    -1.755050   -1.476395   -0.209688
2011-01-04  -0.554705   1.342504    0.245934    0.955521    NaN
2011-01-05  -0.351260   -0.798270   0.820535    -0.597322   0.546146
2011-01-06  0.132924    0.501027    -1.139487   1.107873    NaN

数据的情况(见下文)似乎基本相同 – 将一个数组与DatetimeIndex串联起来,其值是数据帧的一个子集.但是它给出了标题中的ValueError(blah1 =(5,286)blah2 =(5,276)).为什么不工作？

In[187]: df.head()
Out[188]:
high    low loc_h   loc_l
time                
2014-01-01 17:00:00 1.376235    1.375945    1.376235    1.375945
2014-01-01 17:01:00 1.376005    1.375775    NaN NaN
2014-01-01 17:02:00 1.375795    1.375445    NaN 1.375445
2014-01-01 17:03:00 1.375625    1.375515    NaN NaN
2014-01-01 17:04:00 1.375585    1.375585    NaN NaN
In [186]: df.index
Out[186]:
<class 'pandas.tseries.index.DatetimeIndex'>
[2014-01-01 17:00:00,...,2014-01-01 21:30:00]
Length: 271,Freq: None,Timezone: None

In [189]: hl.head()
Out[189]:
2014-01-01 17:00:00    1.376090
2014-01-01 17:02:00    1.375445
2014-01-01 17:05:00    1.376195
2014-01-01 17:10:00    1.375385
2014-01-01 17:12:00    1.376115
dtype: float64

In [187]:hl.index
Out[187]:
<class 'pandas.tseries.index.DatetimeIndex'>
[2014-01-01 17:00:00,2014-01-01 21:30:00]
Length: 89,Timezone: None

In: pd.concat([df,hl],axis=1)
Out: [stack trace] ValueError: Shape of passed values is (5,286),indices imply (5,276)

检查df1和s1中的重复索引值(例如df1.index.is_unique)

删除重复的索引值(例如,df.drop_duplicates(inplace = True))或其中一个方法https://stackoverflow.com/a/34297689/7163376应该解决它.

总结

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