R for 循环遍历向量，如果下标超出范围更改为某个值

Question

I have a vector list where sometimes the values range 1 to 7 and sometimes 1 to 5. I want to loop through them and get frequency count using the function table and then place those values into a data frame, but I receive a subscript out of bounds error. It does this because it expects an integer value. When this happens, I would like to set the integer value to 0.

Is there an easy function I could wrap around the integer value, eg somefunction(t[[6]]) that returns 0 ?

#list of vectors, the first has values 1 to 7, the second has 1 to 5, 
#the third is 1 to 7 again and is only included to show that my real problem has many
# more vectors to evaluate


vectors<-list(c(1,1,2,2,3,3,3,4,4,5,5,5,6,6,6,6,7,7,7,7,7),
c(1,1,2,2,3,3,3,4,4,5,5,5,5,5,5,5,5,5,5,5,5),
c(1,1,2,2,3,3,3,4,4,5,5,5,6,6,6,6,7,7,7,7,7))

#empty data frame
df<-data.frame()
#loop through list of vectors and get frequncy count per list
for (i in 1:length(vectors)) {
  #count frquency of each value as variable t
  t<-table(vectors[[i]])
      #put frequency count of each value in the data frame - the problem is 
      #that in the second vector, there are only values of 1 to 5, so t[[6]] 
      #reports "subscript out of bounds". I want to change this to a value of 0
  df<-rbind(df,cbind(t[[1]],t[[2]],t[[3]],t[[4]],t[[5]],t[[6]],t[[7]]))
}

df

Answer 1

Instead of looping, we can convert the list to a two column data.frame with stack after setting the names of the list and then apply table

table(stack(setNames(vectors, seq_along(vectors)))[2:1])
#  values
#ind  1  2  3  4  5  6  7
#  1  2  2  3  2  3  4  5
#  2  2  2  3  2 12  0  0
#  3  2  2  3  2  3  4  5

The above would be a table object. If we need to convert to data.frame (without reshaping to 'long' format)

as.data.frame.matrix(table(stack(setNames(vectors, seq_along(vectors)))[2:1]))

Here, we apply the table only once and it would be more efficient and less complicated because it automatically finds the unique values. If we are looping, then we have to find the unique values beforehand to add missing levels to be counted as 0

---

With a loop, we can convert the individual list elements to factor with levels specified as the unique of all the elements

un1 <- sort(unique(unlist(vectors)))
t(sapply(vectors, function(x) table(factor(x, levels = un1))))

---

In the for loop, we could use rbind , but with rbind it would expect the column names to be same or the lengths to be same. So, instead of rbind , an option is bind_rows from dplyr

library(dplyr)
df <- data.frame()
for(i in seq_along(vectors)) {
      tbl1 <- table(vectors[[i]])
      df <- bind_rows(df, tbl1)
 }

By default, bind_rows fills with NA for columns that are not found. Then we replace the NA to 0

df[is.na(df)] <- 0

But, this is not an efficient option as the one showed with calling table once