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https://issues.apache.org/jira/browse/SPARK-18178?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon updated SPARK-18178:
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Labels: bulk-closed (was: )
> 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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