Here is the best plot_ly can do:

library(plotly)
library(tidyverse)

dat <- tibble(QuarterYear = c("Q4 2019", "Q4 2019", "Q4 2019", 
                              "Q4 2019", "Q4 2019", "Q4 2019", "Q4 2019", "Q4 2019", "Q4 2019", 
                              "Q4 2019", "Q4 2019", "Q4 2019", "Q1 2020", "Q1 2020", "Q1 2020", 
                              "Q1 2020", "Q1 2020", "Q1 2020", "Q1 2020", "Q1 2020", "Q1 2020", 
                              "Q1 2020", "Q1 2020", "Q1 2020", "Q2 2020", "Q2 2020", "Q2 2020", 
                              "Q2 2020", "Q2 2020", "Q2 2020", "Q2 2020", "Q2 2020", "Q2 2020", 
                              "Q2 2020", "Q2 2020", "Q2 2020", "Q3 2020", "Q3 2020", "Q3 2020", 
                              "Q3 2020", "Q3 2020", "Q3 2020", "Q3 2020", "Q3 2020", "Q3 2020", 
                              "Q3 2020", "Q3 2020", "Q3 2020"), 
              Grade = c("Grade 8", "Grade 8", 
                        "Grade 8", "Grade 9", "Grade 9", "Grade 9", "Grade 10", "Grade 10", 
                        "Grade 10", "Grade 11", "Grade 11", "Grade 11", "Grade 8", "Grade 8", 
                        "Grade 8", "Grade 9", "Grade 9", "Grade 9", "Grade 10", "Grade 10", 
                        "Grade 10", "Grade 11", "Grade 11", "Grade 11", "Grade 8", "Grade 8", 
                        "Grade 8", "Grade 9", "Grade 9", "Grade 9", "Grade 10", "Grade 10", 
                        "Grade 10", "Grade 11", "Grade 11", "Grade 11", "Grade 8", "Grade 8", 
                        "Grade 8", "Grade 9", "Grade 9", "Grade 9", "Grade 10", "Grade 10", 
                        "Grade 10", "Grade 11", "Grade 11", "Grade 11"), 
              Type = c("overallAverage", 
                       "CT", "RT", "overallAverage", "CT", "RT", "overallAverage", "CT", 
                       "RT", "overallAverage", "CT", "RT", "overallAverage", "CT", "RT", 
                       "overallAverage", "CT", "RT", "overallAverage", "CT", "RT", "overallAverage", 
                       "CT", "RT", "overallAverage", "CT", "RT", "overallAverage", "CT", 
                       "RT", "overallAverage", "CT", "RT", "overallAverage", "CT", "RT", 
                       "overallAverage", "CT", "RT", "overallAverage", "CT", "RT", "overallAverage", 
                       "CT", "RT", "overallAverage", "CT", "RT"), 
              value = c(2.48, 2.21, 
                        0.27, 3.48, 3.03, 0.45, 4.6, 4, 0.6, 2.8, 2.4, 0.4, 2.54, 2.28, 
                        0.26, 3.45, 3, 0.45, 4.46, 3.88, 0.58, 3.56, 2.81, 0.75, 2.47, 
                        2.14, 0.33, 2.96, 2.54, 0.41, 4.1, 3.69, 0.41, 3.44, 2.61, 0.83, 
                        2, 1.81, 0.19, 2.54, 2.26, 0.28, 4.11, 3.68, 0.43, 2.67, 2.11, 
                        0.56))

 
 q4_2019 <- dat %>% filter(QuarterYear == "Q4 2019") %>%
  group_by(Grade) %>% 
  arrange(Grade) %>%
  plot_ly(
   x = ~Type, 
   y = ~value, 
   color= ~Grade,
   colors = 'Reds',
   type = 'bar', 
   legendgroup=~Grade) %>% 
  layout(xaxis = list(title = "Q4 2019"))
 
 q1_2020 <- dat %>% filter(QuarterYear == "Q1 2020") %>%
  group_by(Grade) %>% 
  arrange(Grade) %>%
  plot_ly(
   x = ~Type, 
   y = ~value, 
   color= ~Grade,
   colors = 'Reds',
   type = 'bar', 
   legendgroup=~Grade, 
   showlegend = FALSE) %>% 
  layout(xaxis = list(title = "Q1 2020"))
 
 
 q2_2020 <- dat %>% filter(QuarterYear == "Q2 2020") %>%
  group_by(Grade) %>% 
  arrange(Grade) %>%
  plot_ly(
   x = ~Type, 
   y = ~value, 
   color= ~Grade,
   colors = 'Reds',
   type = 'bar', 
   legendgroup=~Grade, 
   showlegend = FALSE) %>% 
  layout(xaxis = list(title = "Q2 2020"))
 
 q3_2020 <- dat %>% filter(QuarterYear == "Q3 2020") %>%
  group_by(Grade) %>% 
  arrange(Grade) %>%
  plot_ly(
   x = ~Type, 
   y = ~value, 
   color= ~Grade,
   colors = 'Reds',
   type = 'bar',
   legendgroup =~Grade,
   showlegend = FALSE) %>% 
  layout(xaxis = list(title = "Q3 2020"))
 
  subplot(q4_2019, q1_2020, q2_2020, q3_2020 ,titleX = TRUE,shareY = T) %>% layout(barmode = 'stack', showlegend = TRUE)