torchwrench.utils.data.dataset.tabular module¶

class torchwrench.utils.data.dataset.tabular.TabularDataset(data: Mapping[Any, SupportsGetitemIterLen] | SupportsGetitemIterLen[dict[Any, Any], Any] | DataFrame | Tensor | ndarray | DynamicItemDataset | TabularDatasetInterface[T_RowIndex, T_ColIndex], row_mapper: Mapping[T_RowIndex, T_RowIndex] | None = None, col_mapper: MutableMapping[T_ColIndex, T_ColIndex] | None = None, fns_list: Iterable[tuple[tuple[T_ColIndex, ...] | T_ColIndex, tuple[T_ColIndex, ...] | T_ColIndex, Callable]] = ())[source]¶

Bases: Generic[T_RowIndex, T_ColIndex], TabularDatasetInterface[T_RowIndex, T_ColIndex]

add_dynamic_column(fn: Callable, requires: tuple[T_ColIndex, ...], provides: T_ColIndex | tuple[T_ColIndex, ...], add_to_output_keys: bool = True) → None[source]¶

property column_names : SupportsGetitemIterLen¶

classmethod from_csv(fpath: str | Path | TextIOBase, **kwds) → Self[source]¶

classmethod from_json(fpath: str | Path | TextIOBase, **kwds) → Self[source]¶

property row_names : SupportsGetitemIterLen¶

to_csv(fpath: str | Path, *args, **kwargs) → None[source]¶

to_dataframe() → DataFrame[source]¶

to_dict_list() → dict[T_ColIndex, list][source]¶

to_json(fpath: str | Path, *args, **kwargs) → None[source]¶

to_list_dict() → list[dict[T_ColIndex, Any]][source]¶

to_numpy() → ndarray[source]¶

to_tensor() → Tensor[source]¶