如何重命名pyspark中的列，类似于使用与Spark兼容的SQL PIVOT语句？

from pyspark.sql import SparkSession

# 创建SparkSession
spark = SparkSession.builder.getOrCreate()

# 创建示例数据
data = [("Alice", 25), ("Bob", 30), ("Charlie", 35)]
df = spark.createDataFrame(data, ["name", "age"])

# 重命名列
df_renamed = df.withColumnRenamed("age", "new_age")

# 显示结果
df_renamed.show()

+-------+-------+
|   name|new_age|
+-------+-------+
|  Alice|     25|
|    Bob|     30|
|Charlie|     35|
+-------+-------+

from pyspark.sql import SparkSession

# 创建SparkSession
spark = SparkSession.builder.getOrCreate()

# 创建示例数据
data = [("Alice", "Math", 90), ("Bob", "Math", 80), ("Charlie", "Science", 85)]
df = spark.createDataFrame(data, ["name", "subject", "score"])

# 使用pivot进行转置
df_pivoted = df.pivot("name").agg({"score": "max"})

# 显示结果
df_pivoted.show()

+-------+-----+-------+
|   name|Alice|    Bob|
+-------+-----+-------+
|  score|   90|     80|
|subject| Math|   Math|
+-------+-----+-------+