Join dataframes - one with multiindex columns and the other without

Question

I'm trying to join two dataframes - one with multiindex columns and the other with a single column name. They have similar index.

I get the following warning: "UserWarning: merging between different levels can give an unintended result (3 levels on the left, 1 on the right)"

For example:

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?

Answer 1

It depends on what you want! Do you want the column from df2 to be aligned with the 1st or second level of columns from df?

You have to add a level to the columns of df2

Super cheezy with pd.concat

df.join(pd.concat([df2], axis=1, keys=['a']))

Better way

df2.columns = pd.MultiIndex.from_product([['a'], df2.columns])

df.join(df2)

Answer 2

I think simpliest is create MultiIndex in df2 and then use concat or 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:

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