ak.to_rdataframe
----------------

.. py:module: ak.to_rdataframe

Defined in `awkward.operations.ak_to_rdataframe <https://github.com/scikit-hep/awkward/blob/f030b8a8ed401e2a19b8045b45e8686f88592e00/src/awkward/operations/ak_to_rdataframe.py>`__ on `line 17 <https://github.com/scikit-hep/awkward/blob/f030b8a8ed401e2a19b8045b45e8686f88592e00/src/awkward/operations/ak_to_rdataframe.py#L17>`__.

.. py:function:: ak.to_rdataframe(arrays, *, flatlist_as_rvec=True)


    :param arrays: Each value in this dict can be any array-like data
               that :py:obj:`ak.to_layout` recognizes, but they must all have the same length.
    :type arrays: dict of arrays
    :param flatlist_as_rvec: If True, lists of primitive types (numbers, booleans, etc.)
                         are presented to C++ as ``ROOT::RVec<primitive>``, but all other types use
                         Awkward Array's custom C++ classes. If False, even these "flat" lists use
                         Awkward Array's custom C++ classes.
    :type flatlist_as_rvec: bool

Converts an Awkward Array into ROOT Data Frame columns:

.. code-block:: python


    >>> x = ak.Array([
    ...     [1.1, 2.2, 3.3],
    ...     [],
    ...     [4.4, 5.5],
    ... ])
    >>> y = ak.Array([
    ...     {"a": 1.1, "b": [1]},
    ...     {"a": 2.2, "b": [2, 1]},
    ...     {"a": 3.3, "b": [3, 2, 1]},
    ... ])

    >>> rdf = ak.to_rdataframe({"x": x, "y": y})
    >>> rdf.Define("z", "ROOT::VecOps::Sum(x) + y.a() + y.b()[0]").AsNumpy(["z"])
    {'z': ndarray([ 8.7,  4.2, 16.2])}

    >>> ak.sum(x, axis=-1) + y.a + y.b[:, 0]
    <Array [8.7, 4.2, 16.2] type='3 * float64'>

See also :py:obj:`ak.from_rdataframe`.