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https://issues.apache.org/jira/browse/SPARK-40063?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Marcelo Rossini Castro updated SPARK-40063:
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Description:
When using the apply function to apply a function to a DataFrame column, it
ends up mixing the column's rows ordering.
A command like this:
{code:java}
df['row_to_apply_function'] = df.apply(lambda row:
func(row['row_to_apply_function']), axis=1){code}
> pyspark.pandas .apply() chaging rows ordering
> ---------------------------------------------
>
> Key: SPARK-40063
> URL: https://issues.apache.org/jira/browse/SPARK-40063
> Project: Spark
> Issue Type: Bug
> Components: Pandas API on Spark
> Affects Versions: 3.3.0
> Reporter: Marcelo Rossini Castro
> Priority: Minor
>
> When using the apply function to apply a function to a DataFrame column, it
> ends up mixing the column's rows ordering.
>
> A command like this:
> {code:java}
> df['row_to_apply_function'] = df.apply(lambda row:
> func(row['row_to_apply_function']), axis=1){code}
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