合并具有多索引的两个数据帧

Question

我已经看过几个关于这个的帖子,但我无法理解merge,join和concat如何解决这个问题.如何合并两个数据帧以查找匹配的索引？

在:

import pandas as pd
import numpy as np
row_x1 = ['a1','b1','c1']
row_x2 = ['a2','b2','c2']
row_x3 = ['a3','b3','c3']
row_x4 = ['a4','b4','c4']
index_arrays = [np.array(['first', 'first', 'second', 'second']), np.array(['one','two','one','two'])]
df1 = pd.DataFrame([row_x1,row_x2,row_x3,row_x4], columns=list('ABC'), index=index_arrays)
print(df1)

出:

             A   B   C
first  one  a1  b1  c1
       two  a2  b2  c2
second one  a3  b3  c3
       two  a4  b4  c4

在:

row_y1 = ['d1','e1','f1']
row_y2 = ['d2','e2','f2']
df2 = pd.DataFrame([row_y1,row_y2], columns=list('DEF'), index=['first','second'])
print(df2)

出

         D   E   F
first   d1  e1  f1
second  d2  e2  f2

换句话说,我如何合并它们来实现df3(如下)？

在

row_x1 = ['a1','b1','c1']
row_x2 = ['a2','b2','c2']
row_x3 = ['a3','b3','c3']
row_x4 = ['a4','b4','c4']
row_y1 = ['d1','e1','f1']
row_y2 = ['d2','e2','f2']

row_z1 = row_x1 + row_y1
row_z2 = row_x2 + row_y1
row_z3 = row_x3 + row_y2
row_z4 = row_x4 + row_y2

df3 = pd.DataFrame([row_z1,row_z2,row_z3,row_z4], columns=list('ABCDEF'), index=index_arrays)
print(df3)

出

             A   B   C   D   E   F
first  one  a1  b1  c1  d1  e1  f1
       two  a2  b2  c2  d1  e1  f1
second one  a3  b3  c3  d2  e2  f2
       two  a4  b4  c4  d2  e2  f2

Answer 1

选项1
使用pd.DataFrame.reindex+ pd.DataFrame.join
reindex有一个方便的level参数,允许您扩展不存在的索引级别.

df1.join(df2.reindex(df1.index, level=0))

             A   B   C   D   E   F
first  one  a1  b1  c1  d1  e1  f1
       two  a2  b2  c2  d1  e1  f1
second one  a3  b3  c3  d2  e2  f2
       two  a4  b4  c4  d2  e2  f2

选项2
您可以重命名轴join并将起作用

df1.rename_axis(['a', 'b']).join(df2.rename_axis('a'))

             A   B   C   D   E   F
a      b                          
first  one  a1  b1  c1  d1  e1  f1
       two  a2  b2  c2  d1  e1  f1
second one  a3  b3  c3  d2  e2  f2
       two  a4  b4  c4  d2  e2  f2

你可以用另一个rename_axis来跟进,以获得理想的结果

df1.rename_axis(['a', 'b']).join(df2.rename_axis('a')).rename_axis([None, None])

             A   B   C   D   E   F
first  one  a1  b1  c1  d1  e1  f1
       two  a2  b2  c2  d1  e1  f1
second one  a3  b3  c3  d2  e2  f2
       two  a4  b4  c4  d2  e2  f2