

def __init__(self, order, name, l, normal_type=InvalidType, blanks_as_nulls=True, infer_types=True):
    '\n        Construct a column from a sequence of values.\n\n        If normal_type is not InvalidType, inference will be skipped and values assumed to have already been normalized.\n        If infer_types is False, type inference will be skipped and the type assumed to be unicode.\n        '
    if (normal_type != InvalidType):
        t = normal_type
        data = l
    elif (not infer_types):
        t = six.text_type
        data = l
    else:
        (t, data) = typeinference.normalize_column_type(l, blanks_as_nulls=blanks_as_nulls)
    list.__init__(self, data)
    self.order = order
    self.name = (name or '_unnamed')
    self.type = t

dataset/ETHPy150Open wireservice/csvkit/csvkit/table.py Column.__init__/original