CODEWITHSUNDEEP
r
Rhys
Rhys

Reputation: 51

How to append unique counter column to a data frame

I have a set of orders with items and where they are sourced from. I need to add a unique counter per order for the item and for the supplier. Note that this unique counter is a unique counter to each order.

library('tidyverse')
library('partitions')

df <- read_table('Order Item Source
1     100 Supplier1
1     101 Supplier1
1     102 Supplier2
1     106 Supplier3
2     107 Supplier4
2     108 Supplier4
3     104 Supplier5
3     103 Supplier6')

The output should look something like this table:

Order Item ItemNum Source SourceNum
    1     100 1 Supplier1 1
    1     101 2 Supplier1 1
    1     102 3 Supplier2 2
    1     106 4 Supplier3 3
    2     107 1 Supplier4 1
    2     108 2 Supplier4 1
    3     104 1 Supplier5 1
    3     103 2 Supplier6 2

Upvotes: 2

Views: 69

Answers (3)

Daniel
Daniel

Reputation: 2229

Consider trying this using group_by and mutate

 df %>% group_by(Order) %>% 
     mutate(ItemNum = row_number(Source),
     SourceNum = cumsum(!duplicated(Source)))


 # A tibble: 8 x 5
 # Groups:   Order [3]
 Order  Item    Source ItemNum SourceNum
 <int> <int>     <chr>   <int>     <int>
  1     1   100 Supplier1       1         1
  2     1   101 Supplier1       2         1
  3     1   102 Supplier2       3         2
  4     1   106 Supplier3       4         3
  5     2   107 Supplier4       1         1
  6     2   108 Supplier4       2         1
  7     3   104 Supplier5       1         1
  8     3   103 Supplier6       2         2

Upvotes: 1

Uwe
Uwe

Reputation: 42544

For the sake of completeness, here is also a data.table solution:

library(data.table)
setDT(df)[, ItemNum := rowid(Order)][
  order(Source), SourceNum := rleid(Source), by = Order][]

   Order Item    Source ItemNum SourceNum
1:     1  100 Supplier1       1         1
2:     1  101 Supplier1       2         1
3:     1  102 Supplier2       3         2
4:     1  106 Supplier3       4         3
5:     2  107 Supplier4       1         1
6:     2  108 Supplier4       2         1
7:     3  104 Supplier5       1         1
8:     3  103 Supplier6       2         2

Upvotes: 1

digEmAll
digEmAll

Reputation: 57210

A possible solution using ave function :

df$ItemNum  <- ave(1:nrow(df),df$Order,FUN=function(x) as.integer(as.factor(df$Item[x]))) 
df$SourceNum <- ave(1:nrow(df),df$Order,FUN=function(x) as.integer(as.factor(df$Source[x]))) 

> df
  Order Item    Source ItemNum SourceNum
1     1  100 Supplier1       1         1
2     1  101 Supplier1       2         1
3     1  102 Supplier2       3         2
4     2  107 Supplier4       1         1
5     1  106 Supplier3       4         3
6     2  108 Supplier4       2         1
7     3  104 Supplier5       2         1
8     3  103 Supplier6       1         2

Note that this code assumes that df$Source and df$Item are characters (not factors).

Upvotes: 0

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