如何合并“pandas”中的部分多重索引

Question

我有两个数据框。有df1多种指标，df2有标准指标。如何通过重复和df2的每次匹配中的值来合并它们。df2.indexdf1.get

例子

import pandas as pd
import numpy as np
idx1 = pd.MultiIndex.from_product([['bar', 'baz', 'foo'],['one','two']])
idx2 = ['bar', 'baz']
df1 = pd.DataFrame(np.random.randn(6, 2), index=idx1, columns=['A', 'B'])
df2 = pd.DataFrame(np.random.randn(2, 1), index=idx2, columns=['C'])

如果df1是

                A         B
bar one  0.690827 -0.627957
    two -0.080936 -1.330712
baz one  1.395178 -0.099748
    two -0.116789  0.723990
foo one  0.313067  0.853808
    two  0.409727 -0.529002

并且df2是

            C
bar -0.773924
baz  0.099662

如何获得合并像？

                A         B         C
bar one  0.690827 -0.627957 -0.773924
    two -0.080936 -1.330712 -0.773924
baz one  1.395178 -0.099748  0.099662
    two -0.116789  0.723990  0.099662
foo one  0.313067  0.853808  NaN
    two  0.409727 -0.529002  NaN

Answer 1

您可以为索引指定名称并在合并中使用该名称，而无需重新索引或重置索引，如下所示

df1.index.set_names(["id_1", "id_2"], inplace=True)
df1.merge(df2, left_on="id_1", right_index=True, how="left")

结果

                   A          B          C
id_1 id_2                                 
bar  one    0.690827  -0.627957  -0.773924
     two   -0.080936  -1.330712  -0.773924
baz  one    1.395178  -0.099748   0.099662
     two   -0.116789   0.723990   0.099662
foo  one    0.313067   0.853808        NaN
     two    0.409727  -0.529002        NaN