Suggestions on how to visualization this data

Question

I was hoping to pick people's brain on better way visualize data that appears like this:

• Two categorical variables
• One continuous variable

I'm trying to visualize this data in way that is more appropriate than heat map. Does anyone have any suggestions?

Here's the code plus data (Note: There are more rows than the example data I have provided.):

test_data <- structure(list(Toys = c("Slinky", "Slinky", "Slinky", "Slinky", 
                                     "Slinky", "Slinky", "Tin Solider", "Tin Solider", "Tin Solider", 
                                     "Tin Solider", "Tin Solider", "Tin Solider", "Hungry Hungry Hippo", 
                                     "Hungry Hungry Hippo", "Hungry Hungry Hippo", "Hungry Hungry Hippo", 
                                     "Hungry Hungry Hippo", "Hungry Hungry Hippo"), 
                            Manufacturer = c("Manufacturer A", "Manufacturer B", "Manufacturer C", "Manufacturer A", "Manufacturer A", 
                                             "Manufacturer A", "Manufacturer B", "Manufacturer B", "Manufacturer B", 
                                             "Manufacturer B", "Manufacturer B", "Manufacturer B", "Manufacturer C", 
                                             "Manufacturer C", "Manufacturer C", "Manufacturer C", "Manufacturer C", 
                                             "Manufacturer C"), 
                            Price = c(5.99, 6.99, 7.99, 9, 6, 5.54, 7, 
                                      9.99, 6.99, 6.75, 8, 7.99, 9.99, 7.99, 5.99, 8.99, 10.99, 9.75)), 
                           class = "data.frame", row.names = c(NA, -18L))

melted_test_data <- reshape::melt(test_data %>% select(Toys,Manufacturer, Price))

library(plotly)
library(scales)
plot_test_data <- melted_test_data %>% 
  ggplot(aes(x = Manufacturer, y = Toys, fill = value)) +
  geom_tile() +
  scale_fill_distiller(palette = 'Accent', label =  label_comma()) + 
  theme(panel.background = element_rect(fill = 'white'), axis.text.x = element_text(angle = 45, hjust = 1), plot.title = element_text(hjust = 0.5)) +
  labs(title ="Price by Manufacturer and Toys", x = "Manufacturers", y = "Manufacturer") +
  guides(fill = guide_colourbar(title = "price($)"))
ggplotly(plot_test_data) 

Answer 1

If you want to make some kind of comparison of cost across the categories and the manufacturer, then you can compare the prices on mean/median.

library(tidyverse)

test_data %>%
  group_by(Toys, Manufacturer) %>%
  summarise(Price=mean(Price)) %>%
  ggplot()+
  geom_bar(aes(x=Manufacturer, y=Price, fill=Toys), stat = 'identity',position = 'dodge')+
  scale_fill_brewer(palette = 'Set1')+
  theme_bw()+
  theme(legend.position = 'top')

Side note:

Significance of the graph?

Hungry Hippo and Tin soldier are made by only 1 Manufacturer while Slinky is produced by all three. Even though it is produced by all the three manufacturers, the average price varies and it is the highest for Manufacturer C.