@classmethod
    def from_csv(cls, f, name='from_csv_table', sniff_limit=None, column_ids=None, blanks_as_nulls=True, column_offset=1, infer_types=True, no_header_row=False, **kwargs):
        """
        Creates a new Table from a file-like object containing CSV data.

        Note: the column_ids argument will cause only those columns with a matching identifier
        to be parsed, type inferred, etc. However, their order/index property will reflect the
        original data (e.g. column 8 will still be "order" 7, even if it's the third column
        in the resulting Table.
        """
        # This bit of nonsense is to deal with "files" from stdin,
        # which are not seekable and thus must be buffered
        contents = f.read()

        # sniff_limit == 0 means do not sniff
        if sniff_limit is None:
            kwargs['dialect'] = sniff_dialect(contents)
        elif sniff_limit > 0:
            kwargs['dialect'] = sniff_dialect(contents[:sniff_limit])

        f = six.StringIO(contents)
        rows = agate.csv.reader(f, **kwargs)

        try:
            if no_header_row:
                # Peek at a row to infer column names from, and put it back on top
                row = next(rows)
                rows = itertools.chain([row], rows)
                headers = make_default_headers(len(row))
            else:
                headers = next(rows)
        except StopIteration:
            # The file is `/dev/null`.
            headers = []
            pass

        if no_header_row or column_ids:
            column_ids = parse_column_identifiers(column_ids, headers, column_offset)
            headers = [headers[c] for c in column_ids]
        else:
            column_ids = range(len(headers))

        data_columns = [[] for c in headers]
        width = len(data_columns)

        for i, row in enumerate(rows):
            j = 0

            for j, d in enumerate(row):
                try:
                    data_columns[j].append(row[column_ids[j]].strip())
                except IndexError:
                    # Non-rectangular data is truncated
                    break

            j += 1

            # Populate remaining columns with None
            while j is not width:
                data_columns[j].append(None)

                j += 1

        columns = []

        for i, c in enumerate(data_columns):
            columns.append(Column(column_ids[i], headers[i], c, blanks_as_nulls=blanks_as_nulls, infer_types=infer_types))

        return Table(columns, name=name)
dataset/ETHPy150Open wireservice/csvkit/csvkit/table.py/Table.from_csv/operator `<` -> `is not`