Suppose you had tabular data that was concatenated into one large vector, and you had to find a way to convert this vector into a dataframe. You could certainly do this manually, but there is a better way.

So suppose you had this raw vector:

```
v<-c(sample(100:200,36,replace=TRUE))
```

You could do this manually- subset into rows, then rbind into df:

```
a<-v[1:6]
b<-v[7:12]
c<-v[13:18]
d<-v[19:24]
e<-v[25:30]
f<-v[31:36]
df<-as.data.frame(rbind(a,b,c,d,e,f))
```

But there’s an easier way to subset.

```
sub<-split(v, ceiling(seq_along(v)/6))
```

So now each row x I need in the data frame can be referenced by sub[x].

```
df<-as.data.frame(list(sub[1:length(sub)]))
```