You are not showing any code for plotting, can you turn this into a REPRoducible EXample (reprex) to exemplify your problem.
To help you get started here is a reprex of how to calculate proportions by employee
library(dplyr)
sample_df <- data.frame(
stringsAsFactors = FALSE,
Employee = c("A","C","B","C","D","A",
"B","C","B","D","A","C","B","A","A","D","C","C",
"C","A","C","B"),
Status = c("PRESENT","PRESENT","PRESENT",
"PRESENT","PRESENT","PRESENT","PRESENT","PRESENT",
"ABSENT","ABSENT","ABSENT","PRESENT","PRESENT",
"PRESENT","ABSENT","ABSENT","PRESENT","ABSENT","ABSENT",
"ABSENT","ABSENT","ABSENT"),
Month_Yr = c("01/2019","01/2019","01/2019",
"02/2019","03/2019","01/2019","03/2019","01/2019",
"01/2019","01/2019","01/2019","02/2019","01/2019",
"02/2019","02/2019","03/2019","01/2019","01/2019",
"01/2019","02/2019","04/2019","01/2019")
)
sample_df %>%
count(Month_Yr, Employee, Status) %>%
group_by(Month_Yr, Employee) %>%
mutate(Prop = n/sum(n))
#> # A tibble: 14 x 5
#> # Groups: Month_Yr, Employee [9]
#> Month_Yr Employee Status n Prop
#> <chr> <chr> <chr> <int> <dbl>
#> 1 01/2019 A ABSENT 1 0.333
#> 2 01/2019 A PRESENT 2 0.667
#> 3 01/2019 B ABSENT 2 0.5
#> 4 01/2019 B PRESENT 2 0.5
#> 5 01/2019 C ABSENT 2 0.4
#> 6 01/2019 C PRESENT 3 0.6
#> 7 01/2019 D ABSENT 1 1
#> 8 02/2019 A ABSENT 2 0.667
#> 9 02/2019 A PRESENT 1 0.333
#> 10 02/2019 C PRESENT 2 1
#> 11 03/2019 B PRESENT 1 1
#> 12 03/2019 D ABSENT 1 0.5
#> 13 03/2019 D PRESENT 1 0.5
#> 14 04/2019 C ABSENT 1 1
Created on 2020-03-17 by the reprex package (v0.3.0.9001)