tiled.adapters.table.TableAdapter
- class tiled.adapters.table.TableAdapter(partitions: DataFrame | DataFrame, structure: TableStructure, *, metadata: Dict[str, str | int | float | bool | Dict[str, Dict[str, str | int | float | bool | Dict[str, JSON] | List[JSON]]] | List[Dict[str, str | int | float | bool | Dict[str, JSON] | List[JSON]]]] | None = None, specs: List[Spec] | None = None)[source]
Wrap a dataframe-like object in an interface that Tiled can serve.
Examples
>>> df = pandas.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}) >>> DataFrameAdapter.from_pandas(df, npartitions=1)
- __init__(partitions: DataFrame | DataFrame, structure: TableStructure, *, metadata: Dict[str, str | int | float | bool | Dict[str, Dict[str, str | int | float | bool | Dict[str, JSON] | List[JSON]]] | List[Dict[str, str | int | float | bool | Dict[str, JSON] | List[JSON]]]] | None = None, specs: List[Spec] | None = None) None[source]
- Parameters:
- partitions
- structure
- metadata
- specs
Methods
__init__(partitions, structure, *[, ...])from_dask_dataframe(ddf[, metadata, specs])from_dict(*args[, metadata, specs, npartitions])from_pandas(*args[, metadata, specs, ...])get(key)items()metadata()read([fields])read_partition(partition[, fields])structure()Attributes
structure_familysupported_storage