ak.argmin
---------

Defined in `awkward.operations.reducers <https://github.com/scikit-hep/awkward-1.0/blob/80bbef0738a6b7928333d7c705ee1b359991de5b/src/awkward/operations/reducers.py>`__ on `line 692 <https://github.com/scikit-hep/awkward-1.0/blob/80bbef0738a6b7928333d7c705ee1b359991de5b/src/awkward/operations/reducers.py#L692>`__.

.. py:function:: ak.argmin(array, axis=None, keepdims=False, mask_identity=True)


    :param array: Data to find the index positions of the minimum values.
    :param axis: If None, combine all values from the array into
             a single scalar result; if an int, group by that axis: ``0`` is the
             outermost, ``1`` is the first level of nested lists, etc., and
             negative ``axis`` counts from the innermost: ``-1`` is the innermost,
             ``-2`` is the next level up, etc.
    :type axis: None or int
    :param keepdims: If False, this reducer decreases the number of
                 dimensions by 1; if True, the reduced values are wrapped in a new
                 length-1 dimension so that the result of this operation may be
                 broadcasted with the original array.
    :type keepdims: bool
    :param mask_identity: If True, reducing over empty lists results in
                      None (an option type); otherwise, reducing over empty lists
                      results in the operation's identity.
    :type mask_identity: bool

Returns the index position of the minimum value in each group of elements
from ``array`` (many types supported, including all Awkward Arrays and
Records). The identity of minimization would be infinity, but argmin
must return the position of the minimum element, which has no value for
empty lists. Therefore, the identity should be masked: the argmin of
an empty list is None. If ``mask_identity=False``, the result would be ``-1``,
which is distinct from all valid index positions, but care should be taken
that it is not misinterpreted as "the last element of the list."

This operation is the same as NumPy's
`argmin <https://docs.scipy.org/doc/numpy/reference/generated/numpy.argmin.html>`__
if all lists at a given dimension have the same length and no None values,
but it generalizes to cases where they do not.

See :py:obj:`ak.sum` for a more complete description of nested list and missing
value (None) handling in reducers.

