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# numpy.all

`numpy.``all`(a, axis=None, out=None)

  Returns True if all elements evaluate to True.

  Parameters: | a : array_like Input array. axis : int, optional Axis over which to perform the operation. If None, use a flattened input array and return a bool. out : ndarray, optional Array into which the result is placed. Its type is preserved and it must be of the right shape to hold the output.
  Returns: | out : ndarray, bool A logical AND is performed along axis, and the result placed in out. If out was not specified, a new output array is created.

  See also

  `ndarray.all`
    equivalent method

  Notes

  Since NaN is not equal to zero, NaN evaluates to True.

  Examples

      >>> np.all([[True,False],[True,True]])
      False

      >>> np.all([[True,False],[True,True]], axis=0)
      array([ True, False], dtype=bool)

      >>> np.all([-1, 4, 5])
      True

      >>> np.all([1.0, np.nan])
      True

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