如何在pyspark中按列划分dataframe进行进一步处理？

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

spark = SparkSession.builder.getOrCreate()

df = spark.read.csv("data.csv", header=True, inferSchema=True)

column1_df = df.select(col("column1"))
column2_df = df.select(col("column2"))

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

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

# 加载数据并创建DataFrame
df = spark.read.csv("data.csv", header=True, inferSchema=True)

# 按列划分DataFrame
column1_df = df.select(col("column1"))
column2_df = df.select(col("column2"))

# 对划分后的DataFrame进行进一步处理
# ...

# 关闭SparkSession对象
spark.stop()