[jira] [Created] (SPARK-14141) Let user specify datatypes of pandas dataframe in toPandas()

["Luke Miner (JIRA)" <ji...@apache.org>]

Luke Miner created SPARK-14141:
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             Summary: 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


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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