Pivot wider in R with multiple columns - r

Question

I am having trouble converting a particular dataset from long to wide.
col1 col2
ID 55.
animal. dog
animal bear
animal rabbit
shape. circle
ID 67.
animal. cat
shape. square
As you can see, some IDs have multiple observations for "animal" and so I want to make multiple columns like this:
ID. animal. animal2 animal3 shape
55. dog bear. rabbit circle
67. cat. NA NA square
Any help is appreciated!

Answer 1

Try this solution.
Most of the work was creating an separate ID column and then creating the unique names for the columns.
library(tidyr)
library(dplyr)
library(vctrs)
df<- structure(list(col1 = c("ID", "animal", "animal", "animal", "shape", "ID", "animal", "shape"),
col2 = c("55.", "dog", "bear", "rabbit", "circle", "67.", "cat", "square")),
class = "data.frame", row.names = c(NA, -8L))
#create the ID column
df$ID <- NA
#find the ID rows
idrows <- which(df$col1 == "ID")
#fill column and delete rows
df$ID[idrows] <- df$col2[idrows]
df <- fill(df, ID, .direction = "down")
df <- df[-idrows, ]
#create unique names in each grouping and the pivot wider
df %>% group_by(ID) %>%
mutate(col1=vec_as_names(col1, repair = "unique")) %>%
mutate(col1=stringr::str_replace( col1, "\\.+1", "")) %>%
ungroup() %>%
pivot_wider(id_cols = "ID", names_from = "col1", values_from = "col2")
ID animal animal...2 animal...3 shape
<chr> <chr> <chr> <chr> <chr>
1 55. dog bear rabbit circle
2 67. cat NA NA square
Another alternatives based on one of your previous questions:
df %>% group_by(ID) %>%
mutate(col1 = paste0(col1, data.table::rowid(col1))) %>%
ungroup() %>%
pivot_wider(id_cols = "ID", names_from = "col1", values_from = "col2")
or
df %>%
pivot_wider(id_cols = "ID", names_from = "col1", values_from = "col2") %>%
unnest_wider( "shape", names_sep = "_") %>% unnest_wider( "animal", names_sep = "_")