I have this df:
> day <- c(1,1,1,1,2,2,2,2,3,3,3,3)
> Salesperson<- c("Chris", "Phil", "Joy", "Jess", "Chris", "Phil", "Joy", "Jess", "Chris", "Phil", "Joy", "Jess")
> Sales<-c(32,54,65,43,87,54,21,65,75,75,47,56)
> df <- cbind(day, Salesperson,Sales)
> df
day Salesperson Sales
[1,] "1" "Chris" "32"
[2,] "1" "Phil" "54"
[3,] "1" "Joy" "65"
[4,] "1" "Jess" "43"
[5,] "2" "Chris" "87"
[6,] "2" "Phil" "54"
[7,] "2" "Joy" "21"
[8,] "2" "Jess" "65"
[9,] "3" "Chris" "75"
[10,] "3" "Phil" "75"
[11,] "3" "Joy" "47"
[12,] "3" "Jess" "56"
I need to compute the percentage of sales per day for each salesperson. I have been trying with dpply or adding a new column with those values, but none of them works. An example:
For day 1, Chris, and sales = 32, the percentage should be 32/(32+54+65+43)
There is no need to use the group_by() and ungroup() multiple times. You can just do this using tidyverse:
day <- c(1,1,1,1,2,2,2,2,3,3,3,3)
Salesperson<- c("Chris", "Phil", "Joy", "Jess", "Chris", "Phil", "Joy", "Jess", "Chris", "Phil", "Joy", "Jess")
Sales<-c(32,54,65,43,87,54,21,65,75,75,47,56)
df <- cbind(day, Salesperson,Sales)
df <- as.data.frame(df)
df$Sales <- as.numeric(as.character(df$Sales))
df %<>%
group_by(day) %>%
mutate(perc = Sales / sum(Sales))
> df
A tibble: 12 x 4
Groups: day [3]
day Salesperson Sales perc
<fct> <fct> <dbl> <dbl>
1 1 Chris 32. 0.165
2 1 Phil 54. 0.278
3 1 Joy 65. 0.335
4 1 Jess 43. 0.222
5 2 Chris 87. 0.383
6 2 Phil 54. 0.238
7 2 Joy 21. 0.0925
8 2 Jess 65. 0.286
9 3 Chris 75. 0.296
10 3 Phil 75. 0.296
11 3 Joy 47. 0.186
12 3 Jess 56. 0.221
PROOF:
df$perc[1] == 32/(32+54+65+43)
gives
[1] TRUE