[jira] [Resolved] (SPARK-18178) Importing Pandas Tables with Missing Values

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-18178?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-18178.
----------------------------------
    Resolution: Incomplete

> Importing Pandas Tables with Missing Values
> -------------------------------------------
>
>                 Key: SPARK-18178
>                 URL: https://issues.apache.org/jira/browse/SPARK-18178
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 2.0.0
>            Reporter: Kevin Mader
>            Priority: Major
>              Labels: bulk-closed
>
> If you import a table with missing values (like below) and create a dataframe from it, everything works fine until the command is actually execute (.first(), or .toPandas(), etc). The problem came up with a much larger table with values that were not NAN, just empty.
> ```
> import pandas as pd
> from io import StringIO
> test_df = pd.read_csv(StringIO(',Scan Options\n15,SAT2\n16,\n'))
> sqlContext.createDataFrame(test_df).registerTempTable('Test')
> o_qry = sqlContext.sql("SELECT * FROM Test LIMIT 1")
> o_qry.first()
> ```



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