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
andexclude
are empty; ifinclude
andexclude
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 orAllStr
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'
orAllCat
.To select Pandas datetimetz dtypes, use
'datetimetz'
or'datetime64[ns, tz]'
.
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