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https://issues.apache.org/jira/browse/SPARK-21163?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16438535#comment-16438535
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Ed Lee commented on SPARK-21163:
Had a question: in Spark 2.2.1, if I do a .toPandas on a Spark DataFrame with
column integer type, the dtypes in pandas is int64. Whereas in in Spark 2.3.0
they ints are converted to int32. I ran the below in Spark 2.2.1 and 2.3.0:
```
df = spark.sparkContext.parallelize([(i, ) for i in [1, 2,
3]]).toDF(["a"]).select(sf.col('a').cast('int')).toPandas()
df.dtypes
```
Is this intended? We ran into as we have unit tests in a project that passed in
Spark 2.2.1 that fail in Spark 2.3.0
Left a comment on github:
[https://github.com/apache/spark/pull/18378/files/d8ba5452539c5fd5b650b7f5e51e467aabc33739#diff-6fc344560230bf0ef711bb9b5573f1faR1775]
> DataFrame.toPandas should respect the data type
> ---
>
> Key: SPARK-21163
> URL: https://issues.apache.org/jira/browse/SPARK-21163
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
>Affects Versions: 2.3.0
>Reporter: Wenchen Fan
>Assignee: Wenchen Fan
>Priority: Major
> Fix For: 2.3.0
>
>
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