Method to_dask_dataframe

dask/array/core.py:1833–1862

Convert dask Array to dask Dataframe Parameters ---------- columns: list or string list of column names if DataFrame, single string if Series index : dask.dataframe.Index, optional An optional *dask* Index to use for the output Series or DataF

(self, columns=None, index=None, meta=None)

        return to_hdf5(filename, datapath, self, **kwargs)

    def to_dask_dataframe(self, columns=None, index=None, meta=None):
        """Convert dask Array to dask Dataframe

        Parameters
        ----------
        columns: list or string
            list of column names if DataFrame, single string if Series
        index : dask.dataframe.Index, optional
            An optional *dask* Index to use for the output Series or DataFrame.

            The default output index depends on whether the array has any unknown
            chunks. If there are any unknown chunks, the output has ``None``
            for all the divisions (one per chunk). If all the chunks are known,
            a default index with known divisions is created.

            Specifying ``index`` can be useful if you're conforming a Dask Array
            to an existing dask Series or DataFrame, and you would like the
            indices to match.
        meta : object, optional
            An optional `meta` parameter can be passed for dask
            to specify the concrete dataframe type to use for partitions of
            the Dask dataframe. By default, pandas DataFrame is used.

        See Also
        --------
        dask.dataframe.from_dask_array
        """
        from dask.dataframe import from_dask_array

        return from_dask_array(self, columns=columns, index=index, meta=meta)

    def to_backend(self, backend: str | None = None, **kwargs):
        """Move to a new Array backend