如何将正则表达式解析为整个spark dataframe而不是每一列？

from pyspark.sql import SparkSession
from pyspark.sql.functions import regexp_replace, concat

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

# 创建示例DataFrame
data = [("John Doe", "john.doe@example.com"),
        ("Jane Smith", "jane.smith@example.com"),
        ("Bob Johnson", "bob.johnson@example.com")]
df = spark.createDataFrame(data, ["name", "email"])

# 定义正则表达式
regex = r"\."

# 将正则表达式应用于每一列，并创建新的列
df_parsed = df.withColumn("parsed", concat(*[regexp_replace(col, regex, "") for col in df.columns]))

# 显示结果
df_parsed.show(truncate=False)

+------------+-----------------------+-----------------------+
|name        |email                  |parsed                 |
+------------+-----------------------+-----------------------+
|John Doe    |john.doe@example.com   |John Doejohn.doe@examplecom|
|Jane Smith  |jane.smith@example.com |Jane Smithjanesmith@examplecom|
|Bob Johnson |bob.johnson@example.com|Bob Johnsonbobjohnson@examplecom|
+------------+-----------------------+-----------------------+