在Apache Spark DataFrame中，如何删除所有非None值都相同的列？

from pyspark.sql.functions import col

distinct_counts = df.agg(*[countDistinct(col(c)).alias(c) for c in df.columns])

columns_to_drop = [c for c in distinct_counts.columns if distinct_counts.select(c).first()[0] == 1]

df = df.drop(*columns_to_drop)

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

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

# 创建示例DataFrame
data = [("Alice", 25, "F", None),
        ("Bob", 30, "M", None),
        ("Charlie", 35, "M", None),
        ("Dave", None, None, None)]
df = spark.createDataFrame(data, ["name", "age", "gender", "address"])

# 删除所有非None值都相同的列
distinct_counts = df.agg(*[countDistinct(col(c)).alias(c) for c in df.columns])
columns_to_drop = [c for c in distinct_counts.columns if distinct_counts.select(c).first()[0] == 1]
df = df.drop(*columns_to_drop)

# 打印结果
df.show()