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Posted to issues@spark.apache.org by "John Ayad (Jira)" <ji...@apache.org> on 2019/11/29 13:21:00 UTC
[jira] [Updated] (SPARK-30082) Zeros are being treated as NaNs
[ https://issues.apache.org/jira/browse/SPARK-30082?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
John Ayad updated SPARK-30082:
------------------------------
Description:
If you attempt to run
{code:java}
df = df.replace(float('nan'), somethingToReplaceWith)
{code}
It will replace all {{0}} s in columns of type {{Integer}}
Example code snippet to repro this:
{code:java}
from pyspark.sql import SQLContext
spark = SQLContext(sc).sparkSession
df = spark.createDataFrame([(1, 0), (2, 3), (3, 0)], ("index", "value"))
df.show()
df = df.replace(float('nan'), 5)
df.show()
{code}
Here's the output I get when I run this code:
{code:java}
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/__ / .__/\_,_/_/ /_/\_\ version 2.4.4
/_/
Using Python version 3.7.5 (default, Nov 1 2019 02:16:32)
SparkSession available as 'spark'.
>>> from pyspark.sql import SQLContext
>>> spark = SQLContext(sc).sparkSession
>>> df = spark.createDataFrame([(1, 0), (2, 3), (3, 0)], ("index", "value"))
>>> df.show()
+-----+-----+
|index|value|
+-----+-----+
| 1| 0|
| 2| 3|
| 3| 0|
+-----+-----+
>>> df = df.replace(float('nan'), 5)
>>> df.show()
+-----+-----+
|index|value|
+-----+-----+
| 1| 5|
| 2| 3|
| 3| 5|
+-----+-----+
>>>
{code}
was:
If you attempt to run
{code}
df = df.replace(float('nan'), somethingToReplaceWith)
{code}
It will replace all {{0}}s in columns of type {{Integer}}
Example code snippet to repro this:
{code}
from pyspark.sql import SQLContext
spark = SQLContext(sc).sparkSession
df = spark.createDataFrame([(1, 0), (2, 3), (3, 0)], ("index", "value"))
df.show()
df = df.replace(float('nan'), 5)
df.show()
{code}
Here's the output I get when I run this code:
{code}
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/__ / .__/\_,_/_/ /_/\_\ version 2.4.4
/_/
Using Python version 3.7.5 (default, Nov 1 2019 02:16:32)
SparkSession available as 'spark'.
>>> from pyspark.sql import SQLContext
>>> spark = SQLContext(sc).sparkSession
>>> df = spark.createDataFrame([(1, 0), (2, 3), (3, 0)], ("index", "value"))
>>> df.show()
+-----+-----+
|index|value|
+-----+-----+
| 1| 0|
| 2| 3|
| 3| 0|
+-----+-----+
>>> df = df.replace(float('nan'), 5)
>>> df.show()
+-----+-----+
|index|value|
+-----+-----+
| 1| 5|
| 2| 3|
| 3| 5|
+-----+-----+
>>>
{code}
> Zeros are being treated as NaNs
> -------------------------------
>
> Key: SPARK-30082
> URL: https://issues.apache.org/jira/browse/SPARK-30082
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.4.4
> Reporter: John Ayad
> Priority: Major
>
> If you attempt to run
> {code:java}
> df = df.replace(float('nan'), somethingToReplaceWith)
> {code}
> It will replace all {{0}} s in columns of type {{Integer}}
> Example code snippet to repro this:
> {code:java}
> from pyspark.sql import SQLContext
> spark = SQLContext(sc).sparkSession
> df = spark.createDataFrame([(1, 0), (2, 3), (3, 0)], ("index", "value"))
> df.show()
> df = df.replace(float('nan'), 5)
> df.show()
> {code}
> Here's the output I get when I run this code:
> {code:java}
> Welcome to
> ____ __
> / __/__ ___ _____/ /__
> _\ \/ _ \/ _ `/ __/ '_/
> /__ / .__/\_,_/_/ /_/\_\ version 2.4.4
> /_/
> Using Python version 3.7.5 (default, Nov 1 2019 02:16:32)
> SparkSession available as 'spark'.
> >>> from pyspark.sql import SQLContext
> >>> spark = SQLContext(sc).sparkSession
> >>> df = spark.createDataFrame([(1, 0), (2, 3), (3, 0)], ("index", "value"))
> >>> df.show()
> +-----+-----+
> |index|value|
> +-----+-----+
> | 1| 0|
> | 2| 3|
> | 3| 0|
> +-----+-----+
> >>> df = df.replace(float('nan'), 5)
> >>> df.show()
> +-----+-----+
> |index|value|
> +-----+-----+
> | 1| 5|
> | 2| 3|
> | 3| 5|
> +-----+-----+
> >>>
> {code}
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