reshape from long to wide of non-categorical values

Question

I need to reshape date from long to wide that has non-categorical values and not the same number of values.

An example of a dataframe:

df_long <- as.data.frame(cbind(c("id A",  "b",    "b",    "d",    "d","id B", "kh",   "kk",   "ip", "id C", "99", "id D", "id E"),c(1,1,1,1,1, 2,2,2,2,3,3,1,1)))

I need this:

df_wide <- as.data.frame(rbind(c("id A", "b", "b", "d", "d"), c("id B", "kh", "kk", "ip", ""), c("id C", "99", "", "", ""), c("id D", "", "", "", ""), c("id E", "", "", "", "")))

I don't know how to reshape this since values are not categorical and not every id has the same number of values.

So I was wondering about reshaping both from long to wide and wide to long of such data.

Thank you for your help!

Answer 1

You could do:

a = aggregate(V1~V2,transform(df_long,V2 = cumsum(grepl("id",V1))),paste,collapse=',')[,2]
read.csv(text=a,header = FALSE,fill = TRUE)
    V1 V2 V3 V4 V5
1 id A  b  b  d  d
2 id B kh kk ip   
3 id C 99         
4 id D            
5 id E   

since you need to transform it back, then you should do:

 f<-read.csv(text = with(df_long,tapply(V1,cumsum(grepl("id",V1)),paste0,collapse=",")), 
              header = FALSE, fill = TRUE,stringsAsFactors = F,na.strings = "")


 print(f,na = "")
    V1 V2 V3 V4 V5
1 id A  b  b  d  d
2 id B kh kk ip   
3 id C 99         
4 id D            
5 id E

Now to transform it back to your long_data, you could do:

with(g <- transform(stack(f),ind = c(row(f))),na.omit(g[order(ind),]))
   values ind
1    id A   1
6       b   1
11      b   1
16      d   1
21      d   1
2    id B   2
7      kh   2
12     kk   2
17     ip   2
3    id C   3
8      99   3
4    id D   4
5    id E   5