R ggplot bubble chart localised bubbles display without in single chart

Question

Hello R/ggplot experts!

R and ggplot learner here.

I was working on a scenerio and was thinking, how I can display the data in best possible way. I need suggestion and direction from you guys.

R reproducible ggplot:

library(ggrepel)

# Create the data frame.
sales_data <- data.frame(
  emp_name <- c("Sam", "Dave", "John", "Harry", "Clark", "Kent", "Kenneth", "Richard", "Clement", "Toby"), 
  month <- as.factor(c("Jan", "Feb", "Mar", "Jan", "Feb", "Mar", "Jan", "Feb", "Mar", "Jan")),
  dept_name <- as.factor(c("Production", "Services", "Support", "Support", "Services", "Production", "Production", "Support", "Support", "Support")), 
  revenue <- c(100, 200, 300, 400, 500, 600, 500, 400, 300, 200)
)

sales_data$month <- factor(sales_data$month, levels = c("Jan", "Feb", "Mar"))

categorical_bubble_chart <-  ggplot(sales_data, aes(x= month, y = dept_name, size = revenue, fill = revenue, label = revenue)) +
  geom_point(shape = 21, show.legend = FALSE) 

categorical_bubble_chart

Output plot is:

So far good! To represent the data in best possible way in present scenerio. Here is what it should look like.

I am having difficulty in understanding following points:

1. How I can show categories of month("Jan", "Feb", "Mar") in between grid lines. Similarly for Departments. So that I can make a grid like region for each of the combination.

2. Right now, all bubbles are overlapping on each other. I want to put bubbles in non-overlapping manner. For that I am thinking to add one more column in my data frame and randomly assign a value such that, it will be used to plot it inside the grid region. But I am finding it difficult to understand, when my x/y are already month and dept_name then what random value I can provide to make each bubble different from each other ?

I have been thinking on it's solution since last 5-6 hours but couldn't find solution. Any direction or suggestion would be highly appreciated and learning for future readers.

Answer 1

As an alternative to the @Wietze314 approach, "quick & dirty" single-chart built:

ggplot(data = sales_data, aes(x = month, y = dept_name)) +
  geom_tile(data = expand.grid(sales_data$month, sales_data$dept_name), 
            aes(x = Var1, y = Var2), fill = NA, col = 'gray50', lty = 2) +
  geom_point(aes(size = revenue, col = revenue), 
             shape = 16, position = position_jitter(seed = 0), show.legend = F) +
  geom_text(aes(label = revenue), vjust = 1.6, position = position_jitter(seed = 0)) +
  theme_bw() +
  theme(
    axis.title = element_blank(),
    axis.ticks = element_blank(),
    plot.background = element_blank(), 
    axis.line = element_blank(), 
    panel.border = element_blank(), 
    panel.grid = element_blank()
    )