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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def groups(self, labels, collect=None):
 """Group rows by multiple columns, count or aggregate others. Args: ``labels``: list of column names (or indices) to group on ``collect``: a function applied to values in other columns for each group Returns: A Table with each row corresponding to a unique combination of values in the columns specified in ``labels``, where the first columns are those specified in ``labels``, followed by a column of counts for each of the unique values. If ``collect`` is provided, a Table is returned with all original columns, each containing values calculated by first grouping rows according to to values in the ``labels`` column, then applying ``collect`` to each set of grouped values in the other columns. Note: The grouped columns will appear first in the result table. If ``collect`` does not accept arguments with one of the column types, that column will be empty in the resulting table. Color | Shape | Amount | Price Red | Round | 4 | 1.3 Green | Rectangular | 6 | 1.3 Blue | Rectangular | 12 | 2 Red | Round | 7 | 1.75 Green | Rectangular | 9 | 1.4 Green | Round | 2 | 1 Color | Shape | count Blue | Rectangular | 1 Green | Rectangular | 2 Green | Round | 1 Red | Round | 2 Color | Shape | Amount sum | Price sum Blue | Rectangular | 12 | 2 Green | Rectangular | 15 | 2.7 Green | Round | 2 | 1 Red | Round | 11 | 3.05 """

        # Assume that a call to groups with one label is a call to group
        if not _is_non_string_iterable(labels):
            return self.group(labels, collect=collect)

        collect = _zero_on_type_error(collect)
        columns = []
        labels = self._as_labels(labels)
        for label in labels:
            if label not in self.labels:
                raise ValueError("All labels must exist in the table")
            columns.append(self._get_column(label))
        grouped = self.group(list(zip(*columns)), lambda s: s)
        grouped._columns.popitem(last=False) # Discard the column of tuples

        # Flatten grouping values and move them to front
        counts = [len(v) for v in grouped[0]]
        for label in labels[::-1]:
            grouped[label] = grouped.apply(_assert_same, label)
            grouped.move_to_start(label)

        # Aggregate other values
        if collect is None:
            count = 'count' if 'count' not in labels else self._unused_label('count')
            return grouped.select(labels).with_column(count, counts)
        else:
            for label in grouped.labels:
                if label in labels:
                    continue
                column = [collect(v) for v in grouped[label]]
                del grouped[label]
                grouped[_collected_label(collect, label)] = column
            return grouped