python polars 0.10.4

Makefile

@@ -1,6 +1,6 @@
 
 changelog-python:
-	docker run -it --env-file .env --rm -v "$(pwd)":/usr/local/src/your-app githubchangeloggenerator/github-changelog-generator -u pola-rs -p project --exclude-labels rust
+	docker run -it --env-file .env --rm -v "$(pwd)":/usr/local/src/your-app githubchangeloggenerator/github-changelog-generator -u pola-rs -p polars --exclude-labels rust
 
 changelog-rust:
-	docker run -it --env-file .env --rm -v "$(pwd)":/usr/local/src/your-app githubchangeloggenerator/github-changelog-generator -u pola-rs -p project --exclude-labels python
+	docker run -it --env-file .env --rm -v "$(pwd)":/usr/local/src/your-app githubchangeloggenerator/github-changelog-generator -u pola-rs -p polars --exclude-labels python

py-polars/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "py-polars"
-version = "0.10.3"
+version = "0.10.4"
 authors = ["ritchie46 <ritchie46@gmail.com>"]
 edition = "2018"
 readme = "README.md"

py-polars/polars/eager/series.py

@@ -485,6 +485,8 @@ def __getitem__(self, item: Any) -> Any:
                     return NotImplemented
                 out = f(item)
                 if self.dtype == List:
+                    if out is None:
+                        return None
                     return wrap_s(out)
                 return out
 

py-polars/src/lazy/apply.rs

@@ -187,6 +187,11 @@ pub fn map_mul(
         // this is a python Series
         let out = call_lambda_with_series_slice(py, s, &lambda, &pypolars);
 
+        // we return an error, because that will become a null value polars lazy apply list
+        if apply_groups && out.is_none(py) {
+            return Err(PolarsError::NoData("".into()))
+        }
+
         // unpack the wrapper in a PySeries
         let py_pyseries = out.getattr(py, "_s").expect(
             "Could net get series attribute '_s'. \

py-polars/tests/test_apply.py

@@ -23,3 +23,19 @@ def test_apply_none():
 
     out = df.select(pl.map(exprs=["a", "b"], f=lambda s: s[0] * s[1]))
     assert out["a"].to_list() == (df["a"] * df["b"]).to_list()
+
+    # check if we can return None
+    def func(s):
+        if s[0][0] == 190:
+            return None
+        else:
+            return s[0]
+
+    out = (
+        df.groupby("g", maintain_order=True).agg(
+            pl.apply(exprs=["a", pl.col("b") ** 4, pl.col("a") / 4], f=func).alias(
+                "multiple"
+            )
+        )
+    )["multiple"]
+    assert out[1] is None