pandas合并索引不起作用

Question

我有两个由groupby操作生成的数据帧(实际上是Series):

bw

l1
Consumer Discretionary         0.118718
Consumer Staples               0.089850
Energy                         0.109988
Financials                     0.159418
Health Care                    0.115060
Industrials                    0.109078
Information Technology         0.200392
Materials                      0.035509
Telecommunications Services    0.030796
Utilities                      0.031190
dtype: float64

和 pw

l1
Consumer Discretionary         0.148655
Consumer Staples               0.067873
Energy                         0.063899
Financials                     0.095689
Health Care                    0.116015
Industrials                    0.181346
Information Technology         0.117715
Materials                      0.043155
Telecommunications Services    0.009550
Utilities                      0.156103
dtype: float64

当我尝试和merge他们使用时

pd.merge(bw,pw,left_index=True,right_index=True)

我收到一个错误

Traceback (most recent call last):
  File "/usr/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2883, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-174-739bb362e06d>", line 1, in <module>
    pd.merge(pw,attr,left_index=True,right_index=True)
  File "/usr/lib/python2.7/dist-packages/pandas/tools/merge.py", line 39, in merge
    return op.get_result()
  File "/usr/lib/python2.7/dist-packages/pandas/tools/merge.py", line 185, in get_result
    join_index, left_indexer, right_indexer = self._get_join_info()
  File "/usr/lib/python2.7/dist-packages/pandas/tools/merge.py", line 251, in _get_join_info
    left_ax = self.left._data.axes[self.axis]
IndexError: list index out of range

但是当我这样做的时候

bw = bw.reset_index()
pw = pw.reset_index()
mrg = pd.merge(pw,bw,on="l1")

有用.它使得我的代码在多次连接迭代中的可读性降低,但是我想知道我做错了什么以及如何让代码的第一个版本merging on indexes工作.

谢谢

Answer 1

将系列更改为DataFrame然后可以合并

merged = pd.merge(pd.DataFrame(bw),pd.DataFrame(pw),left_index=True,right_index=True)
print(merged)

结果:

                                 0_x       0_y
l1                                             
Consumer Discretionary       0.118718  0.118718
Consumer Staples             0.089850  0.089850
Energy                       0.109988  0.109988
Financials                   0.159418  0.159418
Health Care                  0.115060  0.115060
Industrials                  0.109078  0.109078
Information Technology       0.200392  0.200392
Materials                    0.035509  0.222509
Telecommunications Services  0.030796  0.030796
Utilities                    0.031190  0.031190

或者如果要以并行方式执行合并(bw和pw具有相同的索引,相同数量的项目).

c = zip(bw.tolist(),pw.tolist())
merged = pd.DataFrame(c, index=bw.index)

应该有相同的结果.

当你reset_index()是一个系列时,它会变成一个DataFrame(索引到列).这就是为什么你可以在那之后合并.