If you want a list of columns of a certain type, you can use groupby
:
>>> df = pd.DataFrame([[1, 2.3456, 'c', 'd', 78]], columns=list("ABCDE"))
>>> df
A B C D E
0 1 2.3456 c d 78
[1 rows x 5 columns]
>>> df.dtypes
A int64
B float64
C object
D object
E int64
dtype: object
>>> g = df.columns.to_series().groupby(df.dtypes).groups
>>> g
{dtype('int64'): ['A', 'E'], dtype('float64'): ['B'], dtype('O'): ['C', 'D']}
>>> {k.name: v for k, v in g.items()}
{'object': ['C', 'D'], 'int64': ['A', 'E'], 'float64': ['B']}
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