[SPARK-53657][PYTHON][TESTS] Enable doctests for GroupedData.agg

### What changes were proposed in this pull request?
Enable doctests for `GroupedData.agg`, some doctests were skipped due to dependency on pandas/pyarrow installations.

### Why are the changes needed?
to improve test coverage

### Does this PR introduce _any_ user-facing change?
doc-only changes

### How was this patch tested?
ci

### Was this patch authored or co-authored using generative AI tooling?
no

Closes #52404 from zhengruifeng/enable_group_agg_doctest.

Authored-by: Ruifeng Zheng <[email protected]>
Signed-off-by: Ruifeng Zheng <[email protected]>

Author: zhengruifeng

python/pyspark/sql/connect/group.py

@@ -583,9 +583,13 @@ def _test() -> None:
     import doctest
     from pyspark.sql import SparkSession as PySparkSession
     import pyspark.sql.connect.group
+    from pyspark.testing.utils import have_pandas, have_pyarrow
 
     globs = pyspark.sql.connect.group.__dict__.copy()
 
+    if not have_pandas or not have_pyarrow:
+        del pyspark.sql.connect.group.GroupedData.agg.__doc__
+
     globs["spark"] = (
         PySparkSession.builder.appName("sql.connect.group tests")
         .remote(os.environ.get("SPARK_CONNECT_TESTING_REMOTE", "local[4]"))

python/pyspark/sql/group.py

@@ -126,9 +126,8 @@ def agg(self, *exprs: Union[Column, Dict[str, str]]) -> "DataFrame":
 
         Examples
         --------
-        >>> import pandas as pd  # doctest: +SKIP
+        >>> import pandas as pd
         >>> from pyspark.sql import functions as sf
-        >>> from pyspark.sql.functions import pandas_udf
         >>> df = spark.createDataFrame(
         ...      [(2, "Alice"), (3, "Alice"), (5, "Bob"), (10, "Bob")], ["age", "name"])
         >>> df.show()
@@ -166,11 +165,12 @@ def agg(self, *exprs: Union[Column, Dict[str, str]]) -> "DataFrame":
 
         Same as above but uses pandas UDF.
 
-        >>> @pandas_udf('int')  # doctest: +SKIP
+        >>> from pyspark.sql.functions import pandas_udf
+        >>> @pandas_udf('int')
         ... def min_udf(v: pd.Series) -> int:
         ...     return v.min()
         ...
-        >>> df.groupBy(df.name).agg(min_udf(df.age)).sort("name").show()  # doctest: +SKIP
+        >>> df.groupBy(df.name).agg(min_udf(df.age)).sort("name").show()
         +-----+------------+
         | name|min_udf(age)|
         +-----+------------+
@@ -533,8 +533,13 @@ def _test() -> None:
     import doctest
     from pyspark.sql import SparkSession
     import pyspark.sql.group
+    from pyspark.testing.utils import have_pandas, have_pyarrow
 
     globs = pyspark.sql.group.__dict__.copy()
+
+    if not have_pandas or not have_pyarrow:
+        del pyspark.sql.group.GroupedData.agg.__doc__
+
     spark = SparkSession.builder.master("local[4]").appName("sql.group tests").getOrCreate()
     globs["spark"] = spark