使用重叠列名称的Pandas连接多个数据帧？

Question

我有多个(超过2个)数据帧我想合并.它们都共享相同的值列:

In [431]: [x.head() for x in data]
Out[431]: 
[                     AvgStatisticData
DateTime                             
2012-10-14 14:00:00         39.335996
2012-10-14 15:00:00         40.210110
2012-10-14 16:00:00         48.282816
2012-10-14 17:00:00         40.593039
2012-10-14 18:00:00         40.952014,
                      AvgStatisticData
DateTime                             
2012-10-14 14:00:00         47.854712
2012-10-14 15:00:00         55.041512
2012-10-14 16:00:00         55.488026
2012-10-14 17:00:00         51.688483
2012-10-14 18:00:00         57.916672,
                      AvgStatisticData
DateTime                             
2012-10-14 14:00:00         54.171233
2012-10-14 15:00:00         48.718387
2012-10-14 16:00:00         59.978616
2012-10-14 17:00:00         50.984514
2012-10-14 18:00:00         54.924745,
                      AvgStatisticData
DateTime                             
2012-10-14 14:00:00         65.813114
2012-10-14 15:00:00         71.397868
2012-10-14 16:00:00         76.213973
2012-10-14 17:00:00         72.729002
2012-10-14 18:00:00         73.196415,
....etc

我读到join可以处理多个数据帧,但是我得到:

In [432]: data[0].join(data[1:])
...
Exception: Indexes have overlapping values: ['AvgStatisticData']

我试过传递rsuffix=["%i" % (i) for i in range(len(data))]加入并仍然得到相同的错误.我可以通过data以列名称不重叠的方式构建列表来解决此问题,但也许有更好的方法？

Answer 1

In [65]: pd.concat(data, axis=1)
Out[65]:
                     AvgStatisticData  AvgStatisticData  AvgStatisticData  AvgStatisticData
2012-10-14 14:00:00         39.335996         47.854712         54.171233         65.813114
2012-10-14 15:00:00         40.210110         55.041512         48.718387         71.397868
2012-10-14 16:00:00         48.282816         55.488026         59.978616         76.213973
2012-10-14 17:00:00         40.593039         51.688483         50.984514         72.729002
2012-10-14 18:00:00         40.952014         57.916672         54.924745         73.196415

Answer 2

我会尝试pandas.merge使用该suffixes=选项。

import pandas as pd
import datetime as dt

df_1 = pd.DataFrame({'x' : [dt.datetime(2012,10,21) + dt.timedelta(n) for n in range(10)], 'y' : range(10)})
df_2 = pd.DataFrame({'x' : [dt.datetime(2012,10,21) + dt.timedelta(n) for n in range(10)], 'y' : range(10)})
df = pd.merge(df_1, df_2, on='x', suffixes=['_1', '_2'])

我感兴趣的是看看专家们是否有一种更算法的方法来合并数据帧列表。