Function tuple

python/pathway/internals/reducers.py:610–638

Return a tuple containing all the aggregated values. Order of values inside a tuple is consistent across application to many columns. If optional argument skip_nones is set to True, any Nones in aggregated values are omitted from the result. Example: >>> import pathway as pw

(arg: expr.ColumnExpression, *, skip_nones: bool = False)

def tuple(arg: expr.ColumnExpression, *, skip_nones: bool = False):
    """
    Return a tuple containing all the aggregated values. Order of values inside a tuple
    is consistent across application to many columns. If optional argument skip_nones is
    set to True, any Nones in aggregated values are omitted from the result.

    Example:

    >>> import pathway as pw
    >>> t = pw.debug.table_from_markdown('''
    ...    | colA | colB | colC | colD
    ... 1  | valA | -1   |   5  |  4
    ... 2  | valA |  1   |   5  |  7
    ... 3  | valA |  2   |   5  | -3
    ... 4  | valB |  4   |  10  |  2
    ... 5  | valB |  4   |  10  |  6
    ... 6  | valB |  7   |  10  |  1
    ... ''')
    >>> result = t.groupby(t.colA).reduce(
    ...     tuple_B=pw.reducers.tuple(t.colB),
    ...     tuple_C=pw.reducers.tuple(t.colC),
    ...     tuple_D=pw.reducers.tuple(t.colD),
    ... )
    >>> pw.debug.compute_and_print(result, include_id=False)
    tuple_B    | tuple_C      | tuple_D
    (-1, 1, 2) | (5, 5, 5)    | (4, 7, -3)
    (4, 4, 7)  | (10, 10, 10) | (2, 6, 1)
    """
    return _apply_unary_reducer(_tuple(skip_nones), arg, skip_nones=skip_nones)


def count(*args):