DataFrame.select_dtypes

函数接口

DataFrame.select_dtypes(include=None, exclude=None)

Return a subset of the DataFrame's columns based on the column dtypes.

• Parameters:include, exclude:scalar or list-like
  A selection of dtypes or strings to be included/excluded. At least one of these parameters must be supplied.

• Returns: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.

注意

• To select all numeric types, use np.number or '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 datetimes, use np.datetime64, 'datetime' or 'datetime64'

• To select timedeltas, use np.timedelta64, 'timedelta' or 'timedelta64'

• To select Pandas categorical dtypes, use 'category'

• To select Pandas datetimetz dtypes, use 'datetimetz' (new in 0.20.0) or 'datetime64[ns, tz]'

例子

df = pd.DataFrame({'a': [1, 2] * 3,
                   'b': [True, False] * 3,
                   'c': [1.0, 2.0] * 3})
df
        a      b  c
0       1   True  1.0
1       2  False  2.0
2       1   True  1.0
3       2  False  2.0
4       1   True  1.0
5       2  False  2.0

df.select_dtypes(include='bool')
   b
0  True
1  False
2  True
3  False
4  True
5  False

df.select_dtypes(include=['float64'])
   c
0  1.0
1  2.0
2  1.0
3  2.0
4  1.0
5  2.0

df.select_dtypes(exclude=['int64'])
       b    c
0   True  1.0
1  False  2.0
2   True  1.0
3  False  2.0
4   True  1.0
5  False  2.0