Compare headers of dataframes in pandas

Question

I am trying to compare the headers of two pandas dataframes and filter the columns that match. df1 is my big dataframe with two headers, df2 is sort of a dictionary where I have saved every column header I will need from df1.

So if df1 is something like this:

    A         B         C         D
    a         b         c         d
 0.469112 -0.282863 -1.509059 -1.135632
 1.212112 -0.173215  0.119209 -1.044236
-0.861849 -2.104569 -0.494929  1.071804
 0.721555 -0.706771 -1.039575  0.271860
-0.424972  0.567020  0.276232 -1.087401
-0.673690  0.113648 -1.478427  0.524988

and df2 is something like this:

   B         D         E

I need to get the output:

     B          D
 -0.282863  -1.135632
 -0.173215  -1.044236
 -2.104569   1.071804
 -0.706771   0.271860
  0.567020  -1.087401
  0.113648   0.524988

and also a list of the header elements that were not matching:

A      C

as well as elements missing from df1:

E

So far I have tried the iloc command and a lot of different suggestions here on stackoverflow for comparing rows. Since I am comparing the headers though it was not possible.

EDIT: I have tried

df1.columns.intersection(df2.columns)

but the result is:

MultiIndex(levels=[[], []],
           labels=[[], []])

Is this because of the multiple headers?

Answer 1

Here's are couple of methods, for given df1 and df2

In [1041]: df1.columns
Out[1041]: Index([u'A', u'B', u'C', u'D'], dtype='object')

In [1042]: df2.columns
Out[1042]: Index([u'B', u'D', u'E'], dtype='object')

Columns in both df1 and df2

In [1046]: df1.columns.intersection(df2.columns)
Out[1046]: Index([u'B', u'D'], dtype='object')

Columns in df1 not in df2

In [1047]: df1.columns.difference(df2.columns)
Out[1047]: Index([u'A', u'C'], dtype='object')

Columns in df2 not in df1

In [1048]: df2.columns.difference(df1.columns)
Out[1048]: Index([u'E'], dtype='object')