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Posted to issues@spark.apache.org by "Kevin Mader (JIRA)" <ji...@apache.org> on 2016/10/31 13:59:58 UTC
[jira] [Created] (SPARK-18178) Importing Pandas Tables with Missing
Values
Kevin Mader created SPARK-18178:
-----------------------------------
Summary: 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
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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