Question

我已经看过几篇关于此的帖子，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：

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出：

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)

在：

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

出

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)

换句话说，如何将它们合并以实现df3（如下所示）？

在

         D   E   F
first   d1  e1  f1
second  d2  e2  f2

出

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)

Answer 1

选项1
使用pd.DataFrame.reindex + pd.DataFrame.join
reindex有一个方便的level参数，可让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

您可以使用其他rename_axis跟进，以获得所需的结果

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

合并具有多索引的两个数据帧

1 个答案: