Pivot ID's from one column to several one and pair them with another column character

My problem is the following. I have this data frame:

ID <- c(1,2,NA,3,NA,4,NA,NA,5,NA,NA,NA)

Col_1 <- c(NA,45,NA,23,1,2,8,NA,78,12,NA,19)

Objekt.Nr. <- c(1,1,2,1,2,1,2,3,1,2,3,4)

Fahrzeugart <- c("E-Bike", "Fahrrad", "Fahrrad", "Fahrrad", "Bus", "Bus", "Fahrrad", "Auto", "E-Bike", "Fahrrad", "Fahrrad", "Fahrrad")

Col_2 <- c(1,2,3,4,NA,5,6,7,NA,89,10,12)

df <- data.frame(ID,Col_1, Objekt.Nr., Fahrzeugart, Col_2)

I need to transform it so that there is only one row for every ID, not several like there are now. For that, I need to pivot the data frame so that every object Objekt.Nr will correspond to a new column with the Fahrzeugart.

My goal is that the data frame will look like this:

ID <- c(1,2,3,4,5)

Fahrzeug_1 <- c("E-Bike","Fahrrad","Fahrrad","Bus","E-Bike")

Fahrzeug_2 <- c(NA, "Fahrrad", "Bus", "Fahrrad", "Fahrrad")

Fahrzeug_3 <- c(NA,NA,NA, "Auto", "Fahrrad")

Fahrzeug_4 <- c(NA,NA,NA,NA, "Fahrrad")

col_1 <- c(1,(2,3)...) #merged for every ID

same for Col_2

df_wanted <- data.frame(ID,Fahrzeug_1,Fahrzeug_2,Fahrzeug_3,Fahrzeug_4)

I tried using this code, but it will only return binary values for "Fahrzeugart":

df_melted <- melt(df, id.vars = c("ID"), measure.vars = c("Fahrzeugart")) 

df_wanted <- dcast(df_melted, ID ~ Objekt.Nr., value.var = "Fahrzeugart")

Thank you very much!

You can use fill() from the tidyr package to fill in the missing ID values and then pivot_wider() also from the tidyr package to change from long to wide-form.

library(dplyr)
library(tidyr)
ID <- c(1,2,NA,3,NA,4,NA,NA,5,NA,NA,NA)
Objekt.Nr. <- c(1,1,2,1,2,1,2,3,1,2,3,4)
Fahrzeugart <- c("E-Bike", "Fahrrad", "Fahrrad", "Fahrrad", "Bus", "Bus", "Fahrrad", "Auto", "E-Bike", "Fahrrad", "Fahrrad", "Fahrrad")
df <- data.frame(ID, Objekt.Nr., Fahrzeugart)

df %>% 
  fill(ID, .direction="down") %>% 
  pivot_wider(names_from="Objekt.Nr.", values_from = "Fahrzeugart", names_prefix="Fahrzeugart_")
#> # A tibble: 5 × 5
#>      ID Fahrzeugart_1 Fahrzeugart_2 Fahrzeugart_3 Fahrzeugart_4
#>   <dbl> <chr>         <chr>         <chr>         <chr>        
#> 1     1 E-Bike        <NA>          <NA>          <NA>         
#> 2     2 Fahrrad       Fahrrad       <NA>          <NA>         
#> 3     3 Fahrrad       Bus           <NA>          <NA>         
#> 4     4 Bus           Fahrrad       Auto          <NA>         
#> 5     5 E-Bike        Fahrrad       Fahrrad       Fahrrad

^{Created on 2023-02-14 by the reprex package (v2.0.1)}

Edit: what if there are other columns

If you're alright having some list columns in your data, you could do the following:

library(dplyr)
library(tidyr)
ID <- c(1,2,NA,3,NA,4,NA,NA,5,NA,NA,NA)
Col_1 <- c(NA,45,NA,23,1,2,8,NA,78,12,NA,19)
Objekt.Nr. <- c(1,1,2,1,2,1,2,3,1,2,3,4)
Fahrzeugart <- c("E-Bike", "Fahrrad", "Fahrrad", "Fahrrad", "Bus", "Bus", "Fahrrad", "Auto", "E-Bike", "Fahrrad", "Fahrrad", "Fahrrad")
Col_2 <- c(1,2,3,4,NA,5,6,7,NA,89,10,12)
df <- data.frame(ID,Col_1, Objekt.Nr., Fahrzeugart, Col_2)

df %>% 
  fill(ID, .direction="down") %>% 
  pivot_wider(id_cols=ID, 
              names_from="Objekt.Nr.", 
              values_from = "Fahrzeugart", 
              names_prefix="Fahrzeugart_", 
              unused_fn = list)
#> # A tibble: 5 × 7
#>      ID Fahrzeugart_1 Fahrzeugart_2 Fahrzeugart_3 Fahrzeugart_4 Col_1     Col_2 
#>   <dbl> <chr>         <chr>         <chr>         <chr>         <list>    <list>
#> 1     1 E-Bike        <NA>          <NA>          <NA>          <dbl [1]> <dbl> 
#> 2     2 Fahrrad       Fahrrad       <NA>          <NA>          <dbl [2]> <dbl> 
#> 3     3 Fahrrad       Bus           <NA>          <NA>          <dbl [2]> <dbl> 
#> 4     4 Bus           Fahrrad       Auto          <NA>          <dbl [3]> <dbl> 
#> 5     5 E-Bike        Fahrrad       Fahrrad       Fahrrad       <dbl [4]> <dbl>

^{Created on 2023-02-14 by the reprex package (v2.0.1)}