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From Michael Armbrust <mich...@databricks.com>
Subject Re: Check for null in PySpark DataFrame
Date Wed, 01 Jul 2015 19:18:09 GMT
There is an isNotNull function on any column.

df._1.isNotNull

or

from pyspark.sql.functions import *
col("myColumn").isNotNull

On Wed, Jul 1, 2015 at 3:07 AM, Olivier Girardot <ssaboum@gmail.com> wrote:

> I must admit I've been using the same "back to SQL" strategy for now :p
> So I'd be glad to have insights into that too.
>
> Le mar. 30 juin 2015 à 23:28, pedro <ski.rodriguez@gmail.com> a écrit :
>
>> I am trying to find what is the correct way to programmatically check for
>> null values for rows in a dataframe. For example, below is the code using
>> pyspark and sql:
>>
>> df = sqlContext.createDataFrame(sc.parallelize([(1, None), (2, "a"), (3,
>> "b"), (4, None)]))
>> df.where('_2 is not null').count()
>>
>> However, this won't work
>> df.where(df._2 != None).count()
>>
>> It seems there is no native Python way with DataFrames to do this, but I
>> find that difficult to believe and more likely that I am missing the
>> "right
>> way" to do this.
>>
>>
>>
>> --
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>>
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