Working With Missing Values :
> q <- matrix(c(4,3,2,3,4,2,3,4,1,2,4,1,2,4,1,2,3,4,2,4),ncol=4,byrow=T)
> q
[,1] [,2] [,3] [,4]
[1,] 4 3 2 3
[2,] 4 2 3 4
[3,] 1 2 4 1
[4,] 2 4 1 2
[5,] 3 4 2 4
> attr(q,"dim")
[1] 5 4
> w <- rbind (q, matrix(c(1,4,6,8,3,4,5,7),2,4,byrow=T))
> w
[,1] [,2] [,3] [,4]
[1,] 4 3 2 3
[2,] 4 2 3 4
[3,] 1 2 4 1
[4,] 2 4 1 2
[5,] 3 4 2 4
[6,] 1 4 6 8
[7,] 3 4 5 7
> u <- cbind (w, matrix(c(1,2,3,4,5,6,7,8,9,0,1,2,3,4),7,2,byrow=F))
> u
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 4 3 2 3 1 8
[2,] 4 2 3 4 2 9
[3,] 1 2 4 1 3 0
[4,] 2 4 1 2 4 1
[5,] 3 4 2 4 5 2
[6,] 1 4 6 8 6 3
[7,] 3 4 5 7 7 4
> u[2,2]<- Inf
> u[4,2]<- Inf
> u[5,2]<- -Inf
> u[5,3]<- NA
> u[3,3]<- NA
> u
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 4 3 2 3 1 8
[2,] 4 Inf 3 4 2 9
[3,] 1 2 NA 1 3 0
[4,] 2 Inf 1 2 4 1
[5,] 3 -Inf NA 4 5 2
[6,] 1 4 6 8 6 3
[7,] 3 4 5 7 7 4
> nrow(u)
[1] 7
> ncol(u)
[1] 6
> u[,2]
[1] 3 Inf 2 Inf -Inf 4 4
> v1 <- is.inf(u[,2])
> v1
[1] F T F T T F F
> max(u[,2][!v1]) # [Excludes infinite values]
[1] 4
> u[,3]
[1] 2 3 NA 1 NA 6 5
> v2 <- is.na(u[,3])
> v2
[1] F F T F T F F
> max(u[,3][!v2]) # [Excludes Not Available values]
[1] 6
> mean(u[,3][!v2])
[1] 3.4
> dimnames(u)<-list(c("row1","row2","row3","row4","row5","row6","row7"),c("col1","col2",
+ "col3","col4","col5","col6"))
> u
col1 col2 col3 col4 col5 col6
row1 4 3 2 3 1 8
row2 4 Inf 3 4 2 9
row3 1 2 NA 1 3 0
row4 2 Inf 1 2 4 1
row5 3 -Inf NA 4 5 2
row6 1 4 6 8 6 3
row7 3 4 5 7 7 4
> w1<- u[,"col2"]
> w1
row1 row2 row3 row4 row5 row6 row7
3 Inf 2 Inf -Inf 4 4
> is.inf(w1)
row1 row2 row3 row4 row5 row6 row7
F T F T T F F
> w2<- u[,"col3"]
> w2
row1 row2 row3 row4 row5 row6 row7
2 3 NA 1 NA 6 5
> is.na(w2)
row1 row2 row3 row4 row5 row6 row7
F F T F T F F
