You could use np.isreal to check the type of each element (applymap applies a function to each element in the DataFrame):
In [11]: df.applymap(np.isreal)
Out[11]:
a b
item
a True True
b True True
c True True
d False True
e True True
If all in the row are True then they are all numeric:
In [12]: df.applymap(np.isreal).all(1)
Out[12]:
item
a True
b True
c True
d False
e True
dtype: bool
So to get the subDataFrame of rouges, (Note: the negation, ~, of the above finds the ones which have at least one rogue non-numeric):
In [13]: df[~df.applymap(np.isreal).all(1)]
Out[13]:
a b
item
d bad 0.4
You could also find the location of the first offender you could use argmin:
In [14]: np.argmin(df.applymap(np.isreal).all(1))
Out[14]: 'd'
As @CTZhu points out, it may be slightly faster to check whether it's an instance of either int or float (there is some additional overhead with np.isreal):
df.applymap(lambda x: isinstance(x, (int, float)))