pandas 加入数据帧 - 一个有多索引列，另一个没有
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Join dataframes - one with multiindex columns and the other without
提问by Eyal S.
I'm trying to join two dataframes - one with multiindex columns and the other with a single column name. They have similar index.
我正在尝试加入两个数据框 - 一个具有多索引列，另一个具有单个列名。他们有相似的指数。
I get the following warning: "UserWarning: merging between different levels can give an unintended result (3 levels on the left, 1 on the right)"
我收到以下警告：“用户警告：不同级别之间的合并可能会产生意外结果（左侧 3 个级别，右侧 1 个级别）”
For example:
例如：
arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],
['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]
tuples = list(zip(*arrays))
index = pd.MultiIndex.from_tuples(tuples, names=['first', 'second'])
df = pd.DataFrame(np.random.randn(3, 8), index=['A', 'B', 'C'], columns=index)
df2 = pd.DataFrame(np.random.randn(3), index=['A', 'B', 'C'],columns=['w'])
df3 = df.join(df2)
What is the best way to join these two dataframes?
加入这两个数据框的最佳方法是什么？
回答by piRSquared
It depends on what you want! Do you want the column from df2to be aligned with the 1st or second level of columns from df?
这取决于你想要什么！您希望 from 的列与 fromdf2的第一级或第二级列对齐df吗？
You have to add a level to the columns of df2
您必须在列中添加一个级别 df2
Super cheezy with pd.concat
超级俗气的 pd.concat
df.join(pd.concat([df2], axis=1, keys=['a']))
Better way
更好的方法
df2.columns = pd.MultiIndex.from_product([['a'], df2.columns])
df.join(df2)
回答by jezrael
I think simpliest is create MultiIndexin df2and then use concator join:
我认为simpliest是建立MultiIndex在df2，然后使用concat或join：
df2.columns = pd.MultiIndex.from_tuples([('a','w')])
print (df2)
a
w
A -0.562729
B -0.212032
C 0.102451
df2.columns = [['a'], df2.columns]
print (df2)
a
w
A -1.253881
B -0.637752
C 0.907105
df3 = pd.concat([df, df2], axis=1)
Or:
或者：
df3 = df.join(df2)
print (df3)
first bar baz foo qux \
second one two one two one two one
A -0.269667 0.221566 1.138393 0.871762 -0.063132 -1.995682 -0.797885
B -0.456878 0.293350 -1.040748 -1.307871 0.002462 1.580711 -0.198943
C -0.691755 -0.279445 -0.809215 -0.006658 1.452484 0.516414 -0.295961
first a
second two w
A 1.068843 -0.562729
B 1.247057 -0.212032
C -0.345300 0.102451
