ak.local_index
--------------

.. py:module: ak.local_index

Defined in `awkward.operations.ak_local_index <https://github.com/scikit-hep/awkward/blob/36da52cfa8846355c390beb6555eac1d31c27c26/src/awkward/operations/ak_local_index.py>`__ on `line 22 <https://github.com/scikit-hep/awkward/blob/36da52cfa8846355c390beb6555eac1d31c27c26/src/awkward/operations/ak_local_index.py#L22>`__.

.. py:function:: ak.local_index(array, axis=-1, *, highlevel=True, behavior=None, attrs=None)


    :param array: Array-like data (anything :py:obj:`ak.to_layout` recognizes).
    :param axis: The dimension at which this operation is applied. The
             outermost dimension is ``0``, followed by ``1``, etc., and negative
             values count backward from the innermost: ``-1`` is the innermost
             dimension, ``-2`` is the next level up, etc.
    :type axis: int
    :param highlevel: If True, return an :py:obj:`ak.Array`; otherwise, return
                  a low-level :py:obj:`ak.contents.Content` subclass.
    :type highlevel: bool
    :param behavior: Custom :py:obj:`ak.behavior` for the output array, if
                 high-level.
    :type behavior: None or dict
    :param attrs: Custom attributes for the output array, if
              high-level.
    :type attrs: None or dict

For example,

.. code-block:: python


    >>> array = ak.Array([
    ...     [[0.0, 1.1, 2.2], []],
    ...     [[3.3, 4.4]],
    ...     [],
    ...     [[5.5], [], [6.6, 7.7, 8.8, 9.9]]])
    >>> ak.local_index(array, axis=0)
    <Array [0, 1, 2, 3] type='4 * int64'>
    >>> ak.local_index(array, axis=1)
    <Array [[0, 1], [0], [], [0, 1, 2]] type='4 * var * int64'>
    >>> ak.local_index(array, axis=2)
    <Array [[[0, 1, 2], []], ..., [[0], ..., [...]]] type='4 * var * var * int64'>

Note that you can make a Pandas-style MultiIndex by calling this function on
every axis.

.. code-block:: python


    >>> multiindex = ak.zip([ak.local_index(array, i) for i in range(array.ndim)])
    >>> multiindex.show()
    [[[(0, 0, 0), (0, 0, 1), (0, 0, 2)], []],
     [[(1, 0, 0), (1, 0, 1)]],
     [],
     [[(3, 0, 0)], [], [(3, 2, 0), (3, 2, 1), (3, 2, 2), (3, 2, 3)]]]
    >>> ak.flatten(ak.flatten(multiindex)).show()
    [(0, 0, 0),
     (0, 0, 1),
     (0, 0, 2),
     (1, 0, 0),
     (1, 0, 1),
     (3, 0, 0),
     (3, 2, 0),
     (3, 2, 1),
     (3, 2, 2),
     (3, 2, 3)]

But if you're interested in Pandas, you may want to use :py:obj:`ak.to_dataframe` directly.

.. code-block:: python


    >>> ak.to_dataframe(array)
                                values
    entry subentry subsubentry
    0     0        0               0.0
                   1               1.1
                   2               2.2
    1     0        0               3.3
                   1               4.4
    3     0        0               5.5
          2        0               6.6
                   1               7.7
                   2               8.8
                   3               9.9