I am trying to reshape my data frame. I have my data in long columns, and I need to spread that data out into the same row but new columns, as you can see above.
One of the main problems I am running into is creating the new columns. I am going to end up creating almost 300 new columns. In my exact problem I am going to have A1, A2, all the way to A23, same with the other variables, so manually initializing the columns does not seem to be feasible.
Is there a way I can loop or maybe make this a function to create columns and reshape my data frame?
| Column A | Column B |
| -------- | -------- |
| Cell 1 | Cell 2 |
| Cell 3 | Cell 4 |
| Cell 5 | Cell 6 |
| Column A | Column B | Column A1 | Column B1 | Column A2| Column B2|
| -------- | -------- | --------- | --------- | ---------| ---------|
| Cell 1 | Cell 2 | Cell 3 | Cell 4 | Cell 5 | Cell 6 |
df$A1 <- NA #Initializing the new column
df$A1[1] <- df$A[2] #Setting the value in A row 2, to A1 row 1.
We could do it this way. Main features are creating an id column and grouping after pivoting into long format:
library(dplyr)
library(tidyr)
df %>%
mutate(id = row_number()) %>%
pivot_longer(-id) %>%
mutate(name = paste(name, id), .keep = "unused") %>%
pivot_wider(names_from = name, values_from = value)
`ColA 1` `ColB 1` `ColA 2` `ColB 2` `ColA 3` `ColB 3`
<chr> <chr> <chr> <chr> <chr> <chr>
1 Cell 1 Cell 2 Cell 3 Cell 4 Cell 5 Cell 6
example data:
df <- structure(list(ColA = c("Cell 1", "Cell 3", "Cell 5"), ColB = c("Cell 2",
"Cell 4", "Cell 6")), class = "data.frame", row.names = c(NA,
-3L))