PySpark:如何在数据框中为特定列填充NA值？

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

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

# 创建示例数据框
data = [("Alice", 25, None), ("Bob", None, 80), ("Charlie", 30, 90)]
df = spark.createDataFrame(data, ["Name", "Age", "Score"])

# 填充Age列的NA值为0
df = df.fillna({"Age": 0})

# 填充Score列的NA值为-1
df = df.fillna({"Score": -1})

# 显示填充后的数据框
df.show()

+-------+---+-----+
|   Name|Age|Score|
+-------+---+-----+
|  Alice| 25|   -1|
|    Bob|  0|   80|
|Charlie| 30|   90|
+-------+---+-----+