如何在pyspark中分别透视多个列

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

spark = SparkSession.builder.appName("PivotExample").getOrCreate()

data = [(1, "A", 10), (1, "B", 20), (2, "A", 30), (2, "B", 40)]
df = spark.createDataFrame(data, ["id", "category", "value"])
df.show()

+---+--------+-----+
| id|category|value|
+---+--------+-----+
|  1|       A|   10|
|  1|       B|   20|
|  2|       A|   30|
|  2|       B|   40|
+---+--------+-----+

pivot_df = df.groupBy("id").pivot("category").sum("value")
pivot_df.show()

+---+---+---+
| id|  A|  B|
+---+---+---+
|  1| 10| 20|
|  2| 30| 40|
+---+---+---+