Deleting rows when only specific column has NA/missing value

[ANeeK181]

Hi

I have seen docs of drop_missing() and it only drops rows as per drop policy when all or some columns have NA values. I want to drop all rows when certain column (output) has missing values. How to proceed?

[hosseinmoein]

I am not sure I understand. can you show an example?

[ANeeK181]

<style> </style>

A	B	C	D	E	OUTPUT
1	1	1	1	1	1
2	2	2	2	2	2
3	3	3	3	3
4		4		4	4
5	5	5	5	5	5
6	6	6	6	6	6
7	7	7	7	7
8		8	8	8	8
9	9	9	9	9	9
10	10	10		10	10
11	11	11	11	11	11
12	12	12	12	12	12

[ANeeK181]

Imagine dataframe like above; I only want to delete rows where values are missing in OUTPUT column, but dont care about any other columns. So, i just want to drop rows no 3 and 7 since they dont have output label. So if I use drop_policy as any, it will also delete rows 4, 8 and 10 which is not what i want. Hope i am making some sense here

[hosseinmoein]

I see. you need a column-specific drop logic. I do not have that interface currently. You have to do it manually.
But I will put it on my todo list

[hosseinmoein]

Actually I take that back. You can use remove_data_by_sel()

[ANeeK181]

right, i see. I can use std::isnan to check for nan values in functor, and then remove rows contains nan in output column?

[ANeeK181]

still its a good feature to have in drop_missing() if you add it some day. Drop only those rows when some specific column has missing values