fix: Fix unit null rank (pola-rs#18252)

crates/polars-ops/src/series/ops/rank.rs

@@ -65,6 +65,15 @@ unsafe fn rank_impl<F: FnMut(&mut [IdxSize])>(idxs: &IdxCa, neq: &BooleanArray,
 fn rank(s: &Series, method: RankMethod, descending: bool, seed: Option<u64>) -> Series {
     let len = s.len();
     let null_count = s.null_count();
+
+    if null_count == len {
+        let dt = match method {
+            Average => DataType::Float64,
+            _ => IDX_DTYPE,
+        };
+        return Series::full_null(s.name(), s.len(), &dt);
+    }
+
     match len {
         1 => {
             return match method {

py-polars/tests/unit/expr/test_exprs.py

@@ -333,55 +333,6 @@ def test_arr_contains() -> None:
     }
 
 
-def test_rank() -> None:
-    df = pl.DataFrame(
-        {
-            "a": [1, 1, 2, 2, 3],
-        }
-    )
-
-    s = df.select(pl.col("a").rank(method="average").alias("b")).to_series()
-    assert s.to_list() == [1.5, 1.5, 3.5, 3.5, 5.0]
-    assert s.dtype == pl.Float64
-
-    s = df.select(pl.col("a").rank(method="max").alias("b")).to_series()
-    assert s.to_list() == [2, 2, 4, 4, 5]
-    assert s.dtype == pl.get_index_type()
-
-
-def test_rank_so_4109() -> None:
-    # also tests ranks null behavior
-    df = pl.from_dict(
-        {
-            "id": [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4],
-            "rank": [None, 3, 2, 4, 1, 4, 3, 2, 1, None, 3, 4, 4, 1, None, 3],
-        }
-    ).sort(by=["id", "rank"])
-
-    assert df.group_by("id").agg(
-        [
-            pl.col("rank").alias("original"),
-            pl.col("rank").rank(method="dense").alias("dense"),
-            pl.col("rank").rank(method="average").alias("average"),
-        ]
-    ).to_dict(as_series=False) == {
-        "id": [1, 2, 3, 4],
-        "original": [[None, 2, 3, 4], [1, 2, 3, 4], [None, 1, 3, 4], [None, 1, 3, 4]],
-        "dense": [[None, 1, 2, 3], [1, 2, 3, 4], [None, 1, 2, 3], [None, 1, 2, 3]],
-        "average": [
-            [None, 1.0, 2.0, 3.0],
-            [1.0, 2.0, 3.0, 4.0],
-            [None, 1.0, 2.0, 3.0],
-            [None, 1.0, 2.0, 3.0],
-        ],
-    }
-
-
-def test_rank_string_null_11252() -> None:
-    rank = pl.Series([None, "", "z", None, "a"]).rank()
-    assert rank.to_list() == [None, 1.0, 3.0, None, 2.0]
-
-
 def test_logical_boolean() -> None:
     # note, cannot use expressions in logical
     # boolean context (eg: and/or/not operators)

py-polars/tests/unit/operations/test_random.py

@@ -116,27 +116,6 @@ def test_sample_series() -> None:
     assert len(s.sample(n=10, with_replacement=True, seed=0)) == 10
 
 
-def test_rank_random_expr() -> None:
-    df = pl.from_dict(
-        {"a": [1] * 5, "b": [1, 2, 3, 4, 5], "c": [200, 100, 100, 50, 100]}
-    )
-
-    df_ranks1 = df.with_columns(
-        pl.col("c").rank(method="random", seed=1).over("a").alias("rank")
-    )
-    df_ranks2 = df.with_columns(
-        pl.col("c").rank(method="random", seed=1).over("a").alias("rank")
-    )
-    assert_frame_equal(df_ranks1, df_ranks2)
-
-
-def test_rank_random_series() -> None:
-    s = pl.Series("a", [1, 2, 3, 2, 2, 3, 0])
-    assert_series_equal(
-        s.rank("random", seed=1), pl.Series("a", [2, 4, 7, 3, 5, 6, 1], dtype=pl.UInt32)
-    )
-
-
 def test_shuffle_expr() -> None:
     # pl.set_random_seed should lead to reproducible results.
     s = pl.Series("a", range(20))

py-polars/tests/unit/operations/test_rank.py

@@ -0,0 +1,97 @@
+import polars as pl
+from polars.testing import assert_frame_equal, assert_series_equal
+
+
+def test_rank_nulls() -> None:
+    assert pl.Series([]).rank().to_list() == []
+    assert pl.Series([None]).rank().to_list() == [None]
+    assert pl.Series([None, None]).rank().to_list() == [None, None]
+
+
+def test_rank_random_expr() -> None:
+    df = pl.from_dict(
+        {"a": [1] * 5, "b": [1, 2, 3, 4, 5], "c": [200, 100, 100, 50, 100]}
+    )
+
+    df_ranks1 = df.with_columns(
+        pl.col("c").rank(method="random", seed=1).over("a").alias("rank")
+    )
+    df_ranks2 = df.with_columns(
+        pl.col("c").rank(method="random", seed=1).over("a").alias("rank")
+    )
+    assert_frame_equal(df_ranks1, df_ranks2)
+
+
+def test_rank_random_series() -> None:
+    s = pl.Series("a", [1, 2, 3, 2, 2, 3, 0])
+    assert_series_equal(
+        s.rank("random", seed=1), pl.Series("a", [2, 4, 7, 3, 5, 6, 1], dtype=pl.UInt32)
+    )
+
+
+def test_rank_df() -> None:
+    df = pl.DataFrame(
+        {
+            "a": [1, 1, 2, 2, 3],
+        }
+    )
+
+    s = df.select(pl.col("a").rank(method="average").alias("b")).to_series()
+    assert s.to_list() == [1.5, 1.5, 3.5, 3.5, 5.0]
+    assert s.dtype == pl.Float64
+
+    s = df.select(pl.col("a").rank(method="max").alias("b")).to_series()
+    assert s.to_list() == [2, 2, 4, 4, 5]
+    assert s.dtype == pl.get_index_type()
+
+
+def test_rank_so_4109() -> None:
+    # also tests ranks null behavior
+    df = pl.from_dict(
+        {
+            "id": [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4],
+            "rank": [None, 3, 2, 4, 1, 4, 3, 2, 1, None, 3, 4, 4, 1, None, 3],
+        }
+    ).sort(by=["id", "rank"])
+
+    assert df.group_by("id").agg(
+        [
+            pl.col("rank").alias("original"),
+            pl.col("rank").rank(method="dense").alias("dense"),
+            pl.col("rank").rank(method="average").alias("average"),
+        ]
+    ).to_dict(as_series=False) == {
+        "id": [1, 2, 3, 4],
+        "original": [[None, 2, 3, 4], [1, 2, 3, 4], [None, 1, 3, 4], [None, 1, 3, 4]],
+        "dense": [[None, 1, 2, 3], [1, 2, 3, 4], [None, 1, 2, 3], [None, 1, 2, 3]],
+        "average": [
+            [None, 1.0, 2.0, 3.0],
+            [1.0, 2.0, 3.0, 4.0],
+            [None, 1.0, 2.0, 3.0],
+            [None, 1.0, 2.0, 3.0],
+        ],
+    }
+
+
+def test_rank_string_null_11252() -> None:
+    rank = pl.Series([None, "", "z", None, "a"]).rank()
+    assert rank.to_list() == [None, 1.0, 3.0, None, 2.0]
+
+
+def test_rank_series() -> None:
+    s = pl.Series("a", [1, 2, 3, 2, 2, 3, 0])
+
+    assert_series_equal(
+        s.rank("dense"), pl.Series("a", [2, 3, 4, 3, 3, 4, 1], dtype=pl.UInt32)
+    )
+
+    df = pl.DataFrame([s])
+    assert df.select(pl.col("a").rank("dense"))["a"].to_list() == [2, 3, 4, 3, 3, 4, 1]
+
+    assert_series_equal(
+        s.rank("dense", descending=True),
+        pl.Series("a", [3, 2, 1, 2, 2, 1, 4], dtype=pl.UInt32),
+    )
+
+    assert s.rank(method="average").dtype == pl.Float64
+    assert s.rank(method="max").dtype == pl.get_index_type()

py-polars/tests/unit/series/test_series.py

@@ -994,25 +994,6 @@ def test_mode() -> None:
     assert pl.int_range(0, 3, eager=True).mode().to_list() == [2, 1, 0]
 
 
-def test_rank() -> None:
-    s = pl.Series("a", [1, 2, 3, 2, 2, 3, 0])
-
-    assert_series_equal(
-        s.rank("dense"), pl.Series("a", [2, 3, 4, 3, 3, 4, 1], dtype=UInt32)
-    )
-
-    df = pl.DataFrame([s])
-    assert df.select(pl.col("a").rank("dense"))["a"].to_list() == [2, 3, 4, 3, 3, 4, 1]
-
-    assert_series_equal(
-        s.rank("dense", descending=True),
-        pl.Series("a", [3, 2, 1, 2, 2, 1, 4], dtype=UInt32),
-    )
-
-    assert s.rank(method="average").dtype == pl.Float64
-    assert s.rank(method="max").dtype == pl.get_index_type()
-
-
 def test_diff() -> None:
     s = pl.Series("a", [1, 2, 3, 2, 2, 3, 0])
     expected = pl.Series("a", [1, 1, -1, 0, 1, -3])