Produce a new DataFrame with rows ['y', 'z', 'w'] and columns ['a', 'c'], pulling matching values from df — any row or column label not present in the original becomes NaN.

Sample data: df:

   a  b  c
x  1  4  7
y  2  5  8
z  3  6  9