How can I replace numbers by nulls in a DataFrame?

Question

It might be strange, but I was wondering how to replace any number of a whole DataFrame's Column for null using Scala.

Imagine I have a nullable DoubleType column named col. There, I want to replace all numbers different to (1.0 ~ 10.0) by a null.

I tried unsatisfactorily the next code.

val xf = df.na.replace("col", Map(0.0 -> null.asInstanceOf[Double]).toMap)

But, as you realize in Scala when you convert a null into a Double it becomes represented as a 0.0, and this is not what I want. Besides, I can't realize any way to do it with a range of values. Therefore, I am thinking if there is any way to achieve this?

@zero323 No there is no need, I am just pulling out my hairs. — Alberto Bonsanto, Feb 23 '16 at 20:28

score 2 · Accepted Answer · edited May 23 '17 at 12:08

2

How about when clause instead?

import org.apache.spark.sql.functions.when

val df = sc.parallelize(
  (1L, 0.0) :: (2L, 3.6) :: (3L, 12.0) :: (4L, 5.0) ::  Nil
).toDF("id", "val")

df.withColumn("val", when($"val".between(1.0, 10.0), $"val")).show

// +---+----+
// | id| val|
// +---+----+
// |  1|null|
// |  2| 3.6|
// |  3|null|
// |  4| 5.0|
// +---+----+

Any value which doesn't satisfy the predicate (here val BETWEEN 1.0 AND 10.0) will be replaced with NULL.

See also Create new Dataframe with empty/null field values

edited May 23 '17 at 12:08

Community

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answered Feb 23 '16 at 20:35

zero323

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Just to leave it as an informative comment for the future. How would you do if you want to replace others except....? :) – Alberto Bonsanto Feb 23 '16 at 21:00
1

You can replace `$"val".between(1.0, 10.0)` with some other logical expression (`isIn`, `not(isIn)` and so on). – zero323 Feb 23 '16 at 21:02
@AlbertoBonsanto Can I take a moment of you time? – zero323 Feb 23 '16 at 22:41
If so lets switch to chat: https://chat.stackoverflow.com/rooms/103319/discussion-between-alberto-bonsanto-and-zero323 – zero323 Feb 23 '16 at 22:45

How can I replace numbers by nulls in a DataFrame?

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