如何在PySpark DataFrame中将列转置为行？

from pyspark.sql import SparkSession
from pyspark.sql.functions import col, expr

spark = SparkSession.builder.getOrCreate()

data = [("Alice", 25, 100),
        ("Bob", 30, 200),
        ("Charlie", 35, 300)]
df = spark.createDataFrame(data, ["Name", "Age", "Salary"])
df.show()

+-------+---+------+
|   Name|Age|Salary|
+-------+---+------+
|  Alice| 25|   100|
|    Bob| 30|   200|
|Charlie| 35|   300|
+-------+---+------+

pivoted_df = df.select("Name", expr("stack(2, 'Age', Age, 'Salary', Salary) as (Attribute, Value)")) \
               .groupBy("Name") \
               .pivot("Attribute") \
               .agg(expr("coalesce(first(Value), 0)"))
pivoted_df.show()

+-------+---+------+
|   Name|Age|Salary|
+-------+---+------+
|  Alice| 25|   100|
|    Bob| 30|   200|
|Charlie| 35|   300|
+-------+---+------+