如何在pyspark dataframe上应用group by以及在结果对象上进行转换

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

spark = SparkSession.builder.getOrCreate()

data = [("Alice", 25, "A"),
        ("Bob", 30, "B"),
        ("Alice", 35, "A"),
        ("Bob", 40, "B")]
df = spark.createDataFrame(data, ["Name", "Age", "Group"])

grouped_df = df.groupBy("Group").agg({"Age": "avg"})

result_df = grouped_df.withColumnRenamed("avg(Age)", "Average Age")

result_df.show()

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

spark = SparkSession.builder.getOrCreate()

data = [("Alice", 25, "A"),
        ("Bob", 30, "B"),
        ("Alice", 35, "A"),
        ("Bob", 40, "B")]
df = spark.createDataFrame(data, ["Name", "Age", "Group"])

grouped_df = df.groupBy("Group").agg({"Age": "avg"})
result_df = grouped_df.withColumnRenamed("avg(Age)", "Average Age")

result_df.show()