| 2588 | |
| 2589 | |
| 2590 | def test_reduction_method(): |
| 2591 | df = pd.DataFrame({"x": range(50), "y": range(50, 100)}) |
| 2592 | ddf = dd.from_pandas(df, npartitions=4) |
| 2593 | |
| 2594 | chunk = lambda x, val=0: (x >= val).sum() |
| 2595 | agg = lambda x: x.sum() |
| 2596 | |
| 2597 | # Output of chunk is a scalar |
| 2598 | res = ddf.x.reduction(chunk, aggregate=agg) |
| 2599 | assert_eq(res, df.x.count()) |
| 2600 | |
| 2601 | # Output of chunk is a series |
| 2602 | res = ddf.reduction(chunk, aggregate=agg) |
| 2603 | assert res._name == ddf.reduction(chunk, aggregate=agg)._name |
| 2604 | assert_eq(res, df.count()) |
| 2605 | |
| 2606 | # Test with keywords |
| 2607 | res2 = ddf.reduction(chunk, aggregate=agg, chunk_kwargs={"val": 25}) |
| 2608 | assert ( |
| 2609 | res2._name |
| 2610 | == ddf.reduction(chunk, aggregate=agg, chunk_kwargs={"val": 25})._name |
| 2611 | ) |
| 2612 | assert res2._name != res._name |
| 2613 | assert_eq(res2, (df >= 25).sum()) |
| 2614 | |
| 2615 | # Output of chunk is a dataframe |
| 2616 | def sum_and_count(x): |
| 2617 | return pd.DataFrame({"sum": x.sum(), "count": x.count()}) |
| 2618 | |
| 2619 | res = ddf.reduction(sum_and_count, aggregate=lambda x: x.groupby(level=0).sum()) |
| 2620 | |
| 2621 | assert_eq(res, pd.DataFrame({"sum": df.sum(), "count": df.count()})) |
| 2622 | |
| 2623 | |
| 2624 | def test_reduction_method_split_every(): |