本文介绍了PySpark:当另一个列值满足条件时修改列值的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有一个PySpark数据框,其中有两列ID和等级,
I have a PySpark Dataframe that has two columns Id and rank,
+---+----+ | Id|Rank| +---+----+ | a| 5| | b| 7| | c| 8| | d| 1| +---+----+对于每一行,如果排名大于5,我希望将ID替换为其他".
For each row, I'm looking to replace Id with "other" if Rank is larger than 5.
如果我使用伪代码来解释:
If I use pseudocode to explain:
For row in df: if row.Rank>5: then replace(row.Id,"other")结果应类似于
+-----+----+ | Id|Rank| +-----+----+ | a| 5| |other| 7| |other| 8| | d| 1| +-----+----+任何线索如何实现这一目标?谢谢!!!
Any clue how to achieve this? Thanks!!!
要创建此数据框,请执行以下操作:
To create this Dataframe:
df = spark.createDataFrame([('a',5),('b',7),('c',8),('d',1)], ["Id","Rank"])推荐答案
您可以像<
from pyspark.sql.functions import * df\ .withColumn('Id_New',when(df.Rank <= 5,df.Id).otherwise('other'))\ .drop(df.Id)\ .select(col('Id_New').alias('Id'),col('Rank'))\ .show()这将输出显示为-
+-----+----+ | Id|Rank| +-----+----+ | a| 5| |other| 7| |other| 8| | d| 1| +-----+----+更多推荐
PySpark:当另一个列值满足条件时修改列值
发布评论