[R] Identifying and Removing NA Columns and factor Columns with more than x Levels

[arun]

Hi,
For the first part in the two questions, do this:
dat1<-data.frame(Temp=c(5,10,9,15,NA,14,25,21,24,23,21,24,35,35,36,34,32,33),Temp2=c(5,10,9,15,15,14,25,21,24,23,21,24,35,35,36,34,32,33),Month=rep(c("January","February","March","April","May","June"),each=3),Roof=as.factor(rep(1:6,times=3))) 

 dat1[,colMeans(is.na(dat1))!=0]
dat1[,colMeans(is.na(dat1))==0]
#or
 dat1[,complete.cases(t(dat1))]

#Second part of two questions: In your case, it is 32.
 dat1[unlist(lapply(dat1,function(x) length(levels(x))>=4))]
or,
dat1[sapply(dat1,function(x) length(levels(x))>=4)]

#and
 dat1[sapply(dat1,function(x) length(levels(x))<4)]

I guess you wanted this as separate solutions.  
A.K.

----- Original Message -----
From: "Lopez, Dan" <lopez235 at llnl.gov>
To: "R help (r-help at r-project.org)" <r-help at r-project.org>
Cc: 
Sent: Thursday, August 30, 2012 11:38 AM
Subject: [R] Identifying and Removing NA Columns and factor Columns with more than x Levels

Hi,

How do you subset a dataframe so that you only have columns:

1.       that contain one or more NAs?

2.       that contain factors with greater than or equal to 32 levels?

How do you remove from a dataframe columns**

3.       with one or more NA's?

4.       that contain factors with greater than or equal to 32 levels?

** I know how to remove columns at a basic level but I am trying to figure out a more efficient way of performing these particular tasks (my data set has 60 columns).
For NA's I essentially used summary(mtcars) and manually made a note of where NA's appeared than used:
mtcars1<-mtcars1[,!(names(mtcars1)%in% c("hp","wt","vs"))]
I did something similar for factors with greater than x levels only I used str(mtcars) to help me identify them.
BTW I know mtcars doesn't have any of these issues. I just used it as a quick reference.


Dan


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