I hope you're all keeping COVID-free! I'm trying to use pivot_wider to do the same thing as unstack on a simple data frame but without success. I hope someone can set me right. My data has two columns: a "group" column and a numeric values column. I'd like to reshape it so the data values for each group are in two separate columns named with the group names. I haven't found an answer online. The closest thing I've found is when there is also a third ID-type column like here but I don't have a column like that. I'm getting the same three warning messages as in that post. Here's an example, starting with the unstacked data, using pivot_longer to stack it and then trying to get back to where I started with pivot_wider. (Data is generated randomly.)
dd1 <- as.data.frame(matrix(rpois(10, 5), nrow = 5))
dd1
V1 V2
1 2 8
2 6 4
3 5 4
4 4 7
5 6 3
library(tidyverse)
dd2 <- dd1 %>%
pivot_longer(cols = c("V1", "V2"))
dd2
# A tibble: 10 x 2
name value
<chr> <int>
1 V1 2
2 V2 8
3 V1 6
4 V2 4
5 V1 5
6 V2 4
7 V1 4
8 V2 7
9 V1 6
10 V2 3
pivot_longer works nicely. Now back to the start with pivot_wider.
dd2 %>% pivot_wider(names_from = name, values_from = value)
Values are not uniquely identified; output will contain list-cols.
* Use `values_fn = list` to suppress this warning.
* Use `values_fn = length` to identify where the duplicates arise
* Use `values_fn = {summary_fun}` to summarise duplicates
# A tibble: 1 x 2
V1 V2
<list> <list>
1 <int [5]> <int [5]>
I'd appreciate any help to sort this out.
