Pandas 右合并不保留键顺序

Question

请看下面的代码。为什么 df2 和 df3 不同？根据 https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.merge.html

left: use only keys from left frame, similar to a SQL left outer join; preserve key order

right: use only keys from right frame, similar to a SQL right outer join; preserve key order

我觉得正确的合并不会保留键顺序..谢谢!

---

import pandas as pd

print pd.__version__  # 0.20.3

A = pd.DataFrame({'lkey': ['foo1', 'foo2', 'foo4'], 'value': [1, 2, 4]})
B = pd.DataFrame({'rkey': ['foo1', 'foo2', 'foo3', 'foo4'], 'value': [5, 6, 7, 8]})
# A
#    lkey  value
# 0  foo1      1
# 1  foo2      2
# 2  foo4      4
#
# B
#    rkey  value
# 0  foo1      5
# 1  foo2      6
# 2  foo3      7
# 3  foo4      8

print '+++'
df2 = pd.merge(A, B, left_on='lkey', right_on='rkey', how='right', indicator=True)
print df2
#    lkey  value_x  rkey  value_y      _merge
# 0  foo1      1.0  foo1        5        both
# 1  foo2      2.0  foo2        6        both
# 2  foo4      4.0  foo4        8        both
# 3   NaN      NaN  foo3        7  right_only

print '+++'
df3 = pd.merge(B, A, left_on='rkey', right_on='lkey', how='left', indicator=True)
print df3

#    rkey  value_x  lkey  value_y     _merge
# 0  foo1        5  foo1      1.0       both
# 1  foo2        6  foo2      2.0       both
# 2  foo3        7   NaN      NaN  left_only
# 3  foo4        8  foo4      4.0       both

Answer 1

似乎正确的合并会首先将键的交集放在合并数据框的顶部，然后对其进行排序。然后，右侧数据框的“剩余”键将插入到合并数据框的底部。

使用来自 https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html 的修改示例

A = pd.DataFrame({'key1': ['K0', 'K2', 'K0', 'K1'],
                  'A': ['A0', 'A1', 'A2', 'A3'],
                  'B': ['B0', 'B1', 'B2', 'B3']})
B = pd.DataFrame({'key1': ['K0', 'K2', 'K0', 'K0'],
                  'C': ['C0', 'C1', 'C2', 'C3'],
                  'D': ['D0', 'D1', 'D2', 'D3']})
A
  key1   A   B
0   K0  A0  B0
1   K2  A1  B1
2   K0  A2  B2
3   K1  A3  B3

B
  key1   C   D
0   K0  C0  D0
1   K2  C1  D1
2   K0  C2  D2
3   K0  C3  D3

进行左连接保留(数据框 B 的)键顺序

pd.merge(A, B, how='left', on='key1')
  key1   A   B    C    D
0   K0  A0  B0   C0   D0
1   K0  A0  B0   C2   D2
2   K0  A0  B0   C3   D3
3   K2  A1  B1   C1   D1
4   K0  A2  B2   C0   D0
5   K0  A2  B2   C2   D2
6   K0  A2  B2   C3   D3
7   K1  A3  B3  NaN  NaN

但是，切换输入数据帧的右连接给出以下结果:

pd.merge(B, A, how='right', on='key1')
  key1    C    D   A   B
0   K0   C0   D0  A0  B0
1   K0   C2   D2  A0  B0
2   K0   C3   D3  A0  B0
3   K0   C0   D0  A2  B2
4   K0   C2   D2  A2  B2
5   K0   C3   D3  A2  B2
6   K2   C1   D1  A1  B1
7   K1  NaN  NaN  A3  B3