12

我有多个（超过 2 个）要合并的数据框。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']

我尝试过rsuffix=["%i" % (i) for i in range(len(data))]加入但仍然遇到同样的错误。我可以通过data以列名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？

4

2 回答 2

16 
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
于 2012-10-22T09:54:30.100 回答
5

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'])

我有兴趣看看专家是否有更算法的方法来合并数据框列表。

于 2012-10-22T01:54:35.647 回答