The data is like
example<-matrix(NA,40,7)
colnames(example)=c("1month","2month","3month","4month","5month","6month","7month")
example[,1]<-rep(c(1,3,6,2,4,98,5,3,NA),len=40)
example[,2]<-rep(c(2,7,NA,8,2,NA,3,NA),len=40)
example[,3]<-rep(c(5,3,2,NA),len=40)
example[,4]<-rep(c(NA,91,98,52,35,NA),len=40)
example[,5]<-rep(c(3,NA),len=40)
example[,6]<-rep(c(98,NA,NA,123),len=40)
example[,7]<-rep(c(3,51,NA,NA,4,NA,5,NA),len=40)
example<-as.data.frame(example)
I want to remove 'NA' for each column.
I can do it using drop_na function
but !is.na() doesn't work.
example %>% select('1month') %>% drop_na('1month')<- this work
example %>% select('1month') %>% filter(!is.na('1month')) <- this doesn't work. the result for this is under.
I wonder why this doesn't work and there is any way that I can use != or !is.na() function.
Thank you for your help. Sincerely.
1month
1 1
2 3
3 6
4 2
5 4
6 98
7 5
8 3
9 NA
10 1
11 3
12 6
13 2
14 4
15 98
16 5
17 3
18 NA
19 1
20 3
21 6
22 2
23 4
24 98
25 5
26 3
27 NA
28 1
29 3
30 6
31 2
32 4
33 98
34 5
35 3
36 NA
37 1
38 3
39 6
40 2
