I have the following dataframe (s):
s<-read.table(text = "V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
1 0 62 64 44 NA 55 81 66 57 53
2 0 0 65 50 NA 56 79 69 52 55
3 0 0 0 57 NA 62 84 76 65 59
4 0 0 0 0 NA 30 70 61 41 36
5 0 0 0 0 NA NA NA NA NA NA
6 0 0 0 0 0 0 66 63 51 44
7 0 0 0 0 0 0 0 80 72 72
8 0 0 0 0 0 0 0 0 68 64
9 0 0 0 0 0 0 0 0 0 47
10 0 0 0 0 0 0 0 0 0 0 ", header = TRUE)
As can be seen row 5 and column 5 in this case includes only NA and 0 values. I would like to omit them and to keep the order of lines and columns. There might be more column and rows in the same pattern and I would like to do the same. The size of the dataframe might be changed.
The final result would be:
V1 V2 V3 V4 V6 V7 V8 V9 V10
1 0 62 64 44 55 81 66 57 53
2 0 0 65 50 56 79 69 52 55
3 0 0 0 57 62 84 76 65 59
4 0 0 0 0 30 70 61 41 36
6 0 0 0 0 0 66 63 51 44
7 0 0 0 0 0 0 80 72 72
8 0 0 0 0 0 0 0 68 64
9 0 0 0 0 0 0 0 0 47
10 0 0 0 0 0 0 0 0 0
Is there a way to get the omitted row and column number (in this case 5), as well?
We can try
v1 <- colSums(is.na(s))
v2 <- colSums(s==0, na.rm=TRUE)
j1 <- !(v1>0 & (v1+v2)==nrow(s) & v2 >0)
v3 <- rowSums(is.na(s))
v4 <- rowSums(s==0, na.rm=TRUE)
i1 <- !(v3>0 & (v3+v4)==ncol(s) & v3 >0)
s[i1, j1]
# V1 V2 V3 V4 V6 V7 V8 V9 V10
#1 0 62 64 44 55 81 66 57 53
#2 0 0 65 50 56 79 69 52 55
#3 0 0 0 57 62 84 76 65 59
#4 0 0 0 0 30 70 61 41 36
#6 0 0 0 0 0 66 63 51 44
#7 0 0 0 0 0 0 80 72 72
#8 0 0 0 0 0 0 0 68 64
#9 0 0 0 0 0 0 0 0 47
#10 0 0 0 0 0 0 0 0 0
Suppose if we change one of the values in 's'
s$V7[3] <- NA
By running the above code, the output will be
# V1 V2 V3 V4 V6 V7 V8 V9 V10
#1 0 62 64 44 55 81 66 57 53
#2 0 0 65 50 56 79 69 52 55
#3 0 0 0 57 62 NA 76 65 59
#4 0 0 0 0 30 70 61 41 36
#6 0 0 0 0 0 66 63 51 44
#7 0 0 0 0 0 0 80 72 72
#8 0 0 0 0 0 0 0 68 64
#9 0 0 0 0 0 0 0 0 47
#10 0 0 0 0 0 0 0 0 0
NOTE: The OP's condition is includes only NA and 0 values. I would like to omit them