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DataFrame.select_dtypes()

DataFrame.select_dtypes(include=None, exclude=None) [source]

Return a subset of a DataFrame including/excluding columns based on their dtype.

Parameters:

include, exclude : list-like

A list of dtypes or strings to be included/excluded. You must pass in a non-empty sequence for at least one of these.
Returns:

subset : DataFrame

The subset of the frame including the dtypes in include and excluding the dtypes in exclude.
Raises:

ValueError

  • If both of include and exclude are empty
  • If include and exclude have overlapping elements
  • If any kind of string dtype is passed in.

TypeError

  • If either of include or exclude is not a sequence

Notes

  • To select all numeric types use the numpy dtype numpy.number
  • To select strings you must use the object dtype, but note that this will return all object dtype columns
  • See the numpy dtype hierarchy
  • To select Pandas categorical dtypes, use ?category?

Examples

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>>> df = pd.DataFrame({'a': np.random.randn(6).astype('f4'),
...                    'b': [True, False] * 3,
...                    'c': [1.0, 2.0] * 3})
>>> df
        a      b  c
0  0.3962   True  1
1  0.1459  False  2
2  0.2623   True  1
3  0.0764  False  2
4 -0.9703   True  1
5 -1.2094  False  2
>>> df.select_dtypes(include=['float64'])
   c
0  1
1  2
2  1
3  2
4  1
5  2
>>> df.select_dtypes(exclude=['floating'])
       b
0   True
1  False
2   True
3  False
4   True
5  False
doc_Pandas
doc_Pandas
2025-01-10 15:47:30
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