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https://issues.apache.org/jira/browse/SPARK-22980?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16328936#comment-16328936
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Li Jin commented on SPARK-22980:
--------------------------------

I agree with [~cloud_fan]. I thinkĀ it's enough to document each args to the 
user function is a pandas Series.

> Using pandas_udf when inputs are not Pandas's Series or DataFrame
> -----------------------------------------------------------------
>
>                 Key: SPARK-22980
>                 URL: https://issues.apache.org/jira/browse/SPARK-22980
>             Project: Spark
>          Issue Type: Sub-task
>          Components: PySpark
>    Affects Versions: 2.3.0
>            Reporter: Xiao Li
>            Priority: Major
>             Fix For: 2.3.0
>
>
> {noformat}
> from pyspark.sql.functions import pandas_udf
> from pyspark.sql.functions import col, lit
> from pyspark.sql.types import LongType
> df = spark.range(3)
> f = pandas_udf(lambda x, y: len(x) + y, LongType())
> df.select(f(lit('text'), col('id'))).show()
> {noformat}
> {noformat}
> from pyspark.sql.functions import udf
> from pyspark.sql.functions import col, lit
> from pyspark.sql.types import LongType
> df = spark.range(3)
> f = udf(lambda x, y: len(x) + y, LongType())
> df.select(f(lit('text'), col('id'))).show()
> {noformat}
> The results of pandas_udf are different from udf. 



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