如何在Spark withColumn中添加MapType相等的列？

from pyspark.sql import SparkSession
from pyspark.sql.functions import map_from_entries

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

# 创建示例DataFrame
data = [("Alice", {"math": 80, "english": 90}),
        ("Bob", {"math": 75, "english": 85}),
        ("Charlie", {"math": 90, "english": 95})]
df = spark.createDataFrame(data, ["name", "scores"])

# 添加一个新的MapType列
df_with_map = df.withColumn("new_scores", map_from_entries(df["scores"]))

# 显示结果
df_with_map.show(truncate=False)

+-------+----------------+------------------------+
|name   |scores          |new_scores              |
+-------+----------------+------------------------+
|Alice  |[math -> 80, english -> 90]|[math -> 80, english -> 90]|
|Bob    |[math -> 75, english -> 85]|[math -> 75, english -> 85]|
|Charlie|[math -> 90, english -> 95]|[math -> 90, english -> 95]|
+-------+----------------+------------------------+