MCPcopy
hub / github.com/deepchecks/deepchecks / select

Method select

deepchecks/tabular/dataset.py:832–869  ·  view source on GitHub ↗

Filter dataset columns by given params. Parameters ---------- columns : Union[Hashable, List[Hashable], None] Column names to keep. ignore_columns : Union[Hashable, List[Hashable], None] Column names to drop. Returns -------

(
            self: TDataset,
            columns: t.Union[Hashable, t.List[Hashable], None] = None,
            ignore_columns: t.Union[Hashable, t.List[Hashable], None] = None,
            keep_label: bool = False
    )

Source from the content-addressed store, hash-verified

830 )
831
832 def select(
833 self: TDataset,
834 columns: t.Union[Hashable, t.List[Hashable], None] = None,
835 ignore_columns: t.Union[Hashable, t.List[Hashable], None] = None,
836 keep_label: bool = False
837 ) -> TDataset:
838 """Filter dataset columns by given params.
839
840 Parameters
841 ----------
842 columns : Union[Hashable, List[Hashable], None]
843 Column names to keep.
844 ignore_columns : Union[Hashable, List[Hashable], None]
845 Column names to drop.
846
847 Returns
848 -------
849 TDataset
850 horizontally filtered dataset
851
852 Raises
853 ------
854 DeepchecksValueError
855 In case one of columns given don't exists raise error
856 """
857 if (
858 keep_label
859 and isinstance(columns, list)
860 and self.label_name not in columns
861 ):
862 columns = columns[:]
863 columns.append(self.label_name)
864
865 new_data = select_from_dataframe(self._data, columns, ignore_columns)
866 if new_data.equals(self.data):
867 return self
868 else:
869 return self.copy(new_data)
870
871 @classmethod
872 def cast_to_dataset(cls, obj: t.Any) -> 'Dataset':

Callers 15

btFunction · 0.80
wtFunction · 0.80
sFunction · 0.80
MFunction · 0.80
PFunction · 0.80
IFunction · 0.80
gFunction · 0.80

Calls 2

copyMethod · 0.95
select_from_dataframeFunction · 0.90