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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 04:04:17 UTC
[jira] [Updated] (SPARK-14141) Let user specify datatypes of pandas
dataframe in toPandas()
[ https://issues.apache.org/jira/browse/SPARK-14141?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon updated SPARK-14141:
---------------------------------
Labels: bulk-closed (was: )
> Let user specify datatypes of pandas dataframe in toPandas()
> ------------------------------------------------------------
>
> Key: SPARK-14141
> URL: https://issues.apache.org/jira/browse/SPARK-14141
> Project: Spark
> Issue Type: New Feature
> Components: Input/Output, PySpark, SQL
> Reporter: Luke Miner
> Priority: Minor
> Labels: bulk-closed
>
> Would be nice to specify the dtypes of the pandas dataframe during the toPandas() call. Something like:
> bq. pdf = df.toPandas(dtypes={'a': 'float64', 'b': 'datetime64', 'c': 'bool', 'd': 'category'})
> Since dtypes like `category` are more memory efficient, you could potentially load many more rows into a pandas dataframe with this option without running out of memory.
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