Extract column name of first non NA value in each row of my dataframe

Question

My dataframe looks like this:

colnames:

state   city     name_of_company    11/22    11/23    11/24
ga    atlanta     name              NA       NA         1
ny    newyork     name              NA       .75        1

I am trying to create a new column that contains the dates that correspond to the first non NA value in each row. I have no clue how to do this, so any help is greatly appreciated.

There will be more non-NA values after the first non-NA. The non-NA values represent business transactions, so the date of the first value is the date the company opened--which is what i need — Christian, Nov 23 '16 at 21:17

score 3 · Accepted Answer · answered Nov 23 '16 at 22:17

3

No max.col? I am disappointed. ;-)

names(dat[4:6])[max.col(!is.na(dat[4:6]), "first")]
#[1] "11/24" "11/23"

answered Nov 23 '16 at 22:17

thelatemail

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code_is_entropy · Answer 2 · 2016-11-23T21:48:44.937

1

This is one possible solution

df$first_NA <- apply(df,1,function(x) names(which(which(!is.na(x))>3))[1])

edited Nov 23 '16 at 21:48

answered Nov 23 '16 at 21:34

code_is_entropy

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Earlier answer for to get column name of first NA value, I edited it to get the first non-NA value column name. – code_is_entropy Nov 23 '16 at 21:49

Extract column name of first non NA value in each row of my dataframe

2 Answers2