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# numpy.logical_and

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

  Compute the truth value of x1 AND x2 element-wise.

  Parameters: | x1, x2 : array_like Input arrays. x1 and x2 must be of the same shape. 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 Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs For other keyword-only arguments, see the ufunc docs.
  Returns: | y : ndarray or bool Boolean result with the same shape as x1 and x2 of the logical AND operation on corresponding elements of x1 and x2.

  See also

  `logical_or`, `logical_not`, `logical_xor`, `bitwise_and`

  Examples

      >>> np.logical_and(True, False)
      False
      >>> np.logical_and([True, False], [False, False])
      array([False, False], dtype=bool)

      >>> x = np.arange(5)
      >>> np.logical_and(x>1, x<4)
      array([False, False,  True,  True, False], dtype=bool)