pandas_select.column.HasDtype¶

class HasDtype(include=None, exclude=None)[source]¶

Select columns based on the column dtypes.

Parameters

include (scalar or list-like) – A selection of dtypes or strings to be included/excluded. At least one of these parameters must be supplied.
exclude (scalar or list-like) – A selection of dtypes or strings to be included/excluded. At least one of these parameters must be supplied.

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.

Notes

To select all numeric types, use numpy.number, 'number' or :class:`AllNumeric.
To select strings you must use the object, string dtype if pandas version > 1.0.0, or or AllStr
See the numpy dtype hierarchy
To select datetimes, use numpy.datetime64, 'datetime' or 'datetime64'.
To select timedeltas, use numpy.timedelta64, 'timedelta' or 'timedelta64'.
To select Pandas categorical dtypes, use 'category' or AllCat.
To select Pandas datetimetz dtypes, use 'datetimetz' or 'datetime64[ns, tz]'.

See also

pandas.DataFrame.select_dtypes(): base implementation

AllBool, AllNumeric, AllNominal

Examples

>>> df = pd.DataFrame({"a": [1, 2],
...                    "b": [True, False],
...                    "c": [1.0, 2.0]})
>>> df
   a      b    c
0  1   True  1.0
1  2  False  2.0
>>> df[HasDtype("int")]
   a
0  1
1  2
>>> import numpy as np
>>> df[HasDtype(include=np.number, exclude=["int"])]
     c
0  1.0
1  2.0