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# numpy.divmod

numpy.divmod(x1, x2, [out1, out2, ]/, [out=(None, None), ]*, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature]) = <ufunc 'divmod'>

  Return element-wise quotient and remainder simultaneously.

  `np.divmod(x, y)` is equivalent to `(x // y, x % y)`, but faster because it avoids redundant work. It is used to implement the Python built-in function `divmod` on NumPy arrays.

  Parameters:
    x1 array_like

      Dividend array.

    x2 array_like

      Divisor array. If `x1.shape != x2.shape`, they must be broadcastable to a common shape (which becomes the shape of the output).

    out ndarray, None, or tuple of ndarray and None, optional

      A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

    where array_like, optional

      This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default `out=None`, locations within it where the condition is False will remain uninitialized.

    **kwargs

      For other keyword-only arguments, see the ufunc docs.

  Returns:
    out1 ndarray

      Element-wise quotient resulting from floor division. This is a scalar if both x1 and x2 are scalars.

    out2 ndarray

      Element-wise remainder from floor division. This is a scalar if both x1 and x2 are scalars.

  See also

  `floor_divide`

    Equivalent to Python’s `//` operator.

  `remainder`

    Equivalent to Python’s `%` operator.

  `modf`

    Equivalent to `divmod(x, 1)` for positive `x` with the return values switched.

  Examples

      >>> import numpy as np
      >>> np.divmod(np.arange(5), 3)
      (array([0, 0, 0, 1, 1]), array([0, 1, 2, 0, 1]))

  The `divmod` function can be used as a shorthand for `np.divmod` on ndarrays.

      >>> x = np.arange(5)
      >>> divmod(x, 3)
      (array([0, 0, 0, 1, 1]), array([0, 1, 2, 0, 1]))