如何将字符串冒号分隔的列转换为MapType？

from pyspark.sql import SparkSession
from pyspark.sql.functions import split, col, create_map
from pyspark.sql.types import StringType, MapType

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

# 创建示例数据
data = [("key1:value1,key2:value2,key3:value3",)]
df = spark.createDataFrame(data, ["col"])

# 将字符串列拆分为键值对
df = df.withColumn("key_value_pairs", split(col("col"), ","))

# 创建空的Map对象
empty_map = create_map()

# 遍历键值对列表，将键值对添加到Map中
for i in range(1, 4):
    df = df.withColumn(f"key{i}", split(col("key_value_pairs")[i-1], ":")[0])
    df = df.withColumn(f"value{i}", split(col("key_value_pairs")[i-1], ":")[1])
    empty_map = empty_map.put(col(f"key{i}"), col(f"value{i}"))

# 将Map转换为MapType列
df = df.withColumn("map_column", empty_map.cast(MapType(StringType(), StringType())))

# 显示结果
df.show(truncate=False)