How do I output the correct percentages on each bar of my Likert chart?

Question

I'm trying to get my code to output the percentage on top of each individual bar. Right now, the percentages shown below are on the wrong side. My code combines Labels 1 and 2 and Labels 3 and 4, and then outputs those numbers on the incorrect sides.

Is there a function to label those bars correctly? I'm including my code, the data from the .csv file, and the current visualization.

library(ggplot2)
library(reshape)
library(likert)
library(dplyr)

setwd("~/Desktop/")

df <- read.csv("Likert_Test.csv")

df[2:3] <- lapply(df[2:3], as.factor)
colnames(df)[2:3] <- c("cake?", "cookies?")

df[2:3] <- lapply(df[2:3], factor, levels = 1:4)
myplot <- likert(df[2:3], grouping = df$gender)

plot(myplot, centered = FALSE, col = c("#0A2240", "#3474DA", "#C1A783", "#323A45")) +
  scale_y_continuous(labels = function(x) paste0(x, "%")) +
  ggtitle("How much do you like...") +
  theme(legend.title = element_blank(),
        axis.title = element_blank(),
        plot.title = element_text(hjust = 0.5))

    gender      cake         cookies
    Male        3            1    
    Male        2            2         
    Male        2            2
    Male        4            2
    Male        2            3
    Male        2            3
    Male        2            3
    Male        1            1
    Male        4            2
    Female      1            1
    Female      3            1
    Female      3            4
    Female      3            4
    Female      1            1
    Female      4            3
    Female      4            2
    Female      3            2
    Female      2            1
    Female      3            1

Answer 1

Here's a sample answer - using ggplot without the using the likart package.

library(tidyverse)
#> Warning: package 'tibble' was built under R version 3.6.3
#> Warning: package 'dplyr' was built under R version 3.6.3
df <- readr::read_table("gender      cake         cookies
    Male        3            1    
    Male        2            2         
    Male        2            2
    Male        4            2
    Male        2            3
    Male        2            3
    Male        2            3
    Male        1            1
    Male        4            2
    Female      1            1
    Female      3            1
    Female      3            4
    Female      3            4
    Female      1            1
    Female      4            3
    Female      4            2
    Female      3            2
    Female      2            1
    Female      3            1")

df %>%
  pivot_longer(-gender, names_to = "question", values_to = "values") %>%
  group_by(gender, question) %>%
  count(values) %>%
  mutate(
    level = case_when(values %in% c(3, 4) ~ "high",
                      values %in% c(1, 2) ~ "low",
                      TRUE ~ "NA"),
    values = as.character(values),
    total_n = sum(n),
    pct_low = sum(n[level == "low"]) / sum(n),
    pct_high = sum(n[level == "high"]) / sum(n)
  ) %>%
  print() %>%
  ggplot(aes(x = gender, y = n, fill = values)) +
  geom_bar(aes(fill = values), position = position_fill(reverse = TRUE), stat = "identity") +
  scale_fill_manual(values = c("#0A2240", "#3474DA", "#C1A783", "#323A45")) +
  scale_y_continuous(labels = scales::percent_format(),
                     expand = expand_scale(mult = .05)) +
  geom_text(aes(
    y = -.05,
    x = gender,
    label = scales::percent(round(pct_low, 2), accuracy = 1)
  ),
  data = . %>% filter(level == "low")) +
  geom_text(aes(
    y = 1.05,
    x = gender,
    label = scales::percent(round(pct_high, 2), accuracy = 1)
  ),
  data = . %>% filter(level == "high")) +
  coord_flip() +
  facet_wrap(~ question, nrow = 2) +
  theme(
    panel.grid.major = element_blank(),
    panel.grid.minor = element_blank(),
    panel.background = element_blank(),
    axis.line = element_line(colour = "black"),
    plot.title = element_text(hjust = 0.5),
    legend.position = "bottom"
  ) +
  labs(title = "How Much do you like...",
       fill = "",
       x = NULL,
       y = NULL)
#> # A tibble: 15 x 8
#> # Groups:   gender, question [4]
#>    gender question values     n level total_n pct_low pct_high
#>    <chr>  <chr>    <chr>  <int> <chr>   <int>   <dbl>    <dbl>
#>  1 Female cake     1          2 low        10   0.3      0.7  
#>  2 Female cake     2          1 low        10   0.3      0.7  
#>  3 Female cake     3          5 high       10   0.3      0.7  
#>  4 Female cake     4          2 high       10   0.3      0.7  
#>  5 Female cookies  1          5 low        10   0.7      0.3  
#>  6 Female cookies  2          2 low        10   0.7      0.3  
#>  7 Female cookies  3          1 high       10   0.7      0.3  
#>  8 Female cookies  4          2 high       10   0.7      0.3  
#>  9 Male   cake     1          1 low         9   0.667    0.333
#> 10 Male   cake     2          5 low         9   0.667    0.333
#> 11 Male   cake     3          1 high        9   0.667    0.333
#> 12 Male   cake     4          2 high        9   0.667    0.333
#> 13 Male   cookies  1          2 low         9   0.667    0.333
#> 14 Male   cookies  2          4 low         9   0.667    0.333
#> 15 Male   cookies  3          3 high        9   0.667    0.333

^{Created on 2020-04-22 by the reprex package (v0.3.0)}