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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 group(self, column_or_label, collect=None):
 """Group rows by unique values in a column; count or aggregate others. Args: ``column_or_label``: values to group (column label or index, or array) ``collect``: a function applied to values in other columns for each group Returns: A Table with each row corresponding to a unique value in ``column_or_label``, where the first column contains the unique values from ``column_or_label``, and the second contains 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 ``column_or_label``, then applying ``collect`` to each set of grouped values in the other columns. Note: The grouped column 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 | count Blue | 1 Green | 3 Red | 2 Color | Shape max | Amount max | Price max Blue | Rectangular | 12 | 2 Green | Round | 9 | 1.4 Red | Round | 7 | 1.75 Shape | Color sum | Amount sum | Price sum Rectangular | | 27 | 4.7 Round | | 13 | 4.05 """

        # Assume that a call to group with a list of labels is a call to groups
        if _is_non_string_iterable(column_or_label) and \
                len(column_or_label) != self._num_rows:
            return self.groups(column_or_label, collect)

        self = self.copy(shallow=True)
        collect = _zero_on_type_error(collect)

        # Remove column used for grouping
        column = self._get_column(column_or_label)
        if isinstance(column_or_label, str) or isinstance(column_or_label, numbers.Integral):
            column_label = self._as_label(column_or_label)
            del self[column_label]
        else:
            column_label = self._unused_label('group')

        # Group by column
        groups = self.index_by(column)
        keys = sorted(groups.keys())

        # Generate grouped columns
        if collect is None:
            labels = [column_label, 'count' if column_label != 'count' else self._unused_label('count')]
            columns = [keys, [len(groups[k]) for k in keys]]
        else:
            columns, labels = [], []
            for i, label in enumerate(self.labels):
                labels.append(_collected_label(collect, label))
                c = [collect(np.array([row[i] for row in groups[k]])) for k in keys]
                columns.append(c)

        grouped = type(self)().with_columns(zip(labels, columns))
        assert column_label == self._unused_label(column_label)
        grouped[column_label] = keys
        grouped.move_to_start(column_label)
        return grouped