Create a dataframe from vector values and their names-CodePudding

I have a set of 50 vectors and would like to create a dataframe from those 50 vectors values and their names as the following example.

Example with 3 vector, but reality is about 50 vectors.

vector_a<- c("a1","a2", "a3","a4")
vector_cx<- c("1","2","3")
vector_3 <-c("x1","x2")

Expected result.

data.frame(values=c("a1","a2", "a3","a4","1","2","3","x1","x2"),
                vector_names=c("vector_a","vector_a", "vector_a","vector_a","vector_cx","vector_cx","vector_cx","vector_3","vector_3"))

The code above produces the following table.

  values vector_names
1     a1     vector_a
2     a2     vector_a
3     a3     vector_a
4     a4     vector_a
5      1    vector_cx
6      2    vector_cx
7      3    vector_cx
8     x1     vector_3
9     x2     vector_3

CodePudding user response：

Using mget to get vectors into a list, then stack to convert list into a dataframe:

stack(mget(ls(pattern = "^vector_")))
#   values       ind
# 1     x1  vector_3
# 2     x2  vector_3
# 3     a1  vector_a
# 4     a2  vector_a
# 5     a3  vector_a
# 6     a4  vector_a
# 7      1 vector_cx
# 8      2 vector_cx
# 9      3 vector_cx

CodePudding user response：

Definitely a worse answer compared to the above.

You can also use purrr to implement a stack

vector_a<- c("a1","a2", "a3","a4")
vector_cx<- c("1","2","3")
vector_3 <-c("x1","x2")


map2_df(list(vector_a, vector_cx), c(deparse(substitute(vector_a)), deparse(substitute(vector_cx))), ~data.frame(.x) %>% mutate(vector_name = .y))

output -----

  .x vector_name
1 a1    vector_a
2 a2    vector_a
3 a3    vector_a
4 a4    vector_a
5  1   vector_cx
6  2   vector_cx
7  3   vector_cx