ensure that we are arraylike if not already

def _ensure_arraylike(values):
    """
    ensure that we are arraylike if not already
    """
    if not is_array_like(values):
        inferred = lib.infer_dtype(values, skipna=False)
        if inferred in ['mixed', 'string', 'unicode']:
            if isinstance(values, tuple):
                values = list(values)
            values = construct_1d_object_array_from_listlike(values)
        else:
            values = np.asarray(values)
    return values