[R] deleting columns from a dataframe where NA is more than 15 percent of the column length

arun smartpink111 at yahoo.com
Mon Aug 6 04:21:25 CEST 2012


HI,

Try this:
dat1<-data.frame(x=c(NA,NA,rnorm(6,15),NA),y=c(NA,rnorm(8,15)),z=c(rnorm(7,15),NA,NA))
dat1[which(colMeans(is.na(dat1))<=.15)]    
     y
1       NA
2 13.53085
3 12.89453
4 15.02625
5 14.00387
6 15.34618
7 15.69293
8 15.62377
9 14.76479

#You can also use apply, sapply etc.
dat2<-data.frame(x=c(NA,NA,rnorm(6,15),NA),y=c(NA,rnorm(8,15)),z=c(rnorm(7,15),NA,NA),u=c(rnorm(9,15)))
dat2[apply(dat2,2,function(x) mean(is.na(x))<=.15)]  

#dat2[sapply(dat2,function(x) mean(is.na(x))<=.15)]
#dat2[which(colMeans(is.na(dat2))<=.15)] 

       y        u
1       NA 14.56278
2 16.49940 16.25761
3 14.11368 14.08768
4 14.95139 14.01923
5 14.99517 15.91936
6 14.46359 14.07573
7 15.09702 13.94888
8 15.99967 14.97171
9 15.51924 15.59981

A.K.





----- Original Message -----
From: Faz Jones <jonesfaz4 at gmail.com>
To: r-help at r-project.org
Cc: 
Sent: Sunday, August 5, 2012 9:04 PM
Subject: [R] deleting columns from a dataframe where NA is more than 15 percent of the column length

I have a dataframe of 10 different columns (length of each column is
the same). I want to eliminate any column that has 'NA' greater than
15% of the column length. Do i first need to make a function for
calculating the percentage of NA for each column and then make another
dataframe where i apply the function? Whats the best way to do this.

______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.




More information about the R-help mailing list