def isnumeric(ds):
    """ Has a numeric measure

    >>> isnumeric('int32')
    True
    >>> isnumeric('3 * ?real')
    True
    >>> isnumeric('string')
    False
    >>> isnumeric('var * {amount: ?int32}')
    False
    """
    ds = launder(ds)

    try:
        npdtype = to_numpy_dtype(ds)
    except TypeError:
        return False
    else:
        return isinstance(ds, Unit) or np.issubdtype(npdtype, np.number)
dataset/ETHPy150Open blaze/datashape/datashape/predicates.py/isnumeric/operator `and` -> `or`