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Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2019/10/08 05:42:14 UTC
[jira] [Resolved] (SPARK-24835) col function ignores drop
[ https://issues.apache.org/jira/browse/SPARK-24835?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-24835.
----------------------------------
Resolution: Incomplete
> col function ignores drop
> -------------------------
>
> Key: SPARK-24835
> URL: https://issues.apache.org/jira/browse/SPARK-24835
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.3.0
> Environment: Spark 2.3.0
> Python 3.5.3
> Reporter: Michael Souder
> Priority: Minor
> Labels: bulk-closed
>
> Not sure if this is a bug or user error, but I've noticed that accessing columns with the col function ignores a previous call to drop.
> {code}
> import pyspark.sql.functions as F
> df = spark.createDataFrame([(1,3,5), (2, None, 7), (0, 3, 2)], ['a', 'b', 'c'])
> df.show()
> +---+----+---+
> | a| b| c|
> +---+----+---+
> | 1| 3| 5|
> | 2|null| 7|
> | 0| 3| 2|
> +---+----+---+
> df = df.drop('c')
> # the col function is able to see the 'c' column even though it has been dropped
> df.where(F.col('c') < 6).show()
> +---+---+
> | a| b|
> +---+---+
> | 1| 3|
> | 0| 3|
> +---+---+
> # trying the same with brackets on the data frame fails with the expected error
> df.where(df['c'] < 6).show()
> Py4JJavaError: An error occurred while calling o36909.apply.
> : org.apache.spark.sql.AnalysisException: Cannot resolve column name "c" among (a, b);{code}
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