如何为以下语句编写等效的 pyspark 代码？

Question

    X_train[var] = np.where(X_train[var].isin(frequent_ls), X_train[var], 'Rare')

如何用 pyspark sql 函数替换 numpy？

Answer 1

你定义一个udf函数

from spark.sql import function as F
from pyspark.sql.types import StringType()

def dictonnary(x):
    if x in frequent_ls: 
        return x 
    else:
        return "rare"

replace = F.udf(lambda x: dictionnary(x), StrungType())

Xtrain = xtrain.withColumn("var2", replace(F.col("var")))

Answer 2

您可以简单地使用 .isin 运算符：

import pyspark.sql.functions as F

X_train = (X_train
           .withColumn(var, F.when(X_train[var].isin(frequent_ls), X_train[var]).otherwise('Rare'))

如何为以下语句编写等效的 pyspark 代码？

How do I write an equivalent pyspark code for the following staement?

python

pyspark

pyspark-sql