Styjun

A newbie here.
I have plotted a chart using geom_raster as given below(data.frame created just for illustration):

require(ggplot2)
library(ggrepel)

# Create the data frame.
sales_data <- data.frame(
 emp_name = rep(c("Sam", "Dave", "John", "Harry", "Clark", "Kent", "Kenneth", "Richard", "Clement", "Toby", "Jonathan"), times = 3), 
 month = as.factor(rep(c("Jan", "Feb", "Mar", "Jan", "Feb", "Mar", "Jan", "Feb", "Mar", "Jan", "Jan"), times = 3)),
 dept_name = as.factor(rep(c("Production", "Services", "Support", "Support", "Services", "Production", "Production", "Support", "Support", "Support", "Production"), times = 3)), 
 revenue = rep(c(100, 200, 300, 400, 500, 600, 500, 400, 300, 200, 500), times = 3),
 status = rep(c("Low", "Medium", "Medium", "High", "Very High", "Very High", "Very High", "High", "Medium", "Medium", "Low"), times = 3)
)

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

sales_data$status <- factor(sales_data$status, levels = c("Low", "Medium", "High", "Very High"))
sales_data$month <- as.integer(sales_data$month)

ggplot(sales_data, aes(x = month, y = dept_name)) +
 geom_raster(data = expand.grid(sales_data$month, sales_data$dept_name),
 aes(x = Var1, y = Var2, width=1, height=1), fill = NA, col = 'gray50', lty = 1) + #default width and height is 1
 #SAFE: geom_point(aes(size = revenue, col = revenue), 
 # shape = 16, position = position_jitter(seed = 0), show.legend = F) +
 geom_point(aes(size = status, colour = cut(revenue, c(-Inf, 199, 301, Inf)) ), 
 shape = 16, position = position_jitter(seed = 0), show.legend = F) +
 scale_color_manual(name = "revenue", 
 values = c("(-Inf,199]" = "red",
 "(199,301]" = "#ffbf00", #amber
 "(301, Inf]" = "green") ) +
 geom_text(aes(label = revenue), size=4, vjust = 1.6, position = position_jitter(seed = 0)) + #try with geom_text

 #geom_rect(aes(xmin = 0.5, xmax = 3.5, ymin = -1, ymax = 0.5), fill = "grey", alpha = 0.03)+
 #annotate("text", x=0.5, y=-1, label= "Chart title", fontface =2) +
 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(),

 axis.text = element_text(colour = "blue", face = "plain", size =11)
 ) +
 #coord_polar(start = 0.5, clip = 'off') +

 scale_x_continuous(limits=c(0.5,3.5), expand = c(0,0), breaks = 1:length(month_vector), labels = month_vector) +

 # Remove extra whitespace from y-axis so lines are against the axis
 scale_y_discrete(expand = c(0,0)) +
 # Add straight lines at each factor level, shifted left/down so they're between values
 geom_hline(yintercept = as.numeric(sales_data$dept_name) + 0.5) +
 geom_vline(xintercept = as.numeric(sales_data$month) - 0.5, color = "grey")

Output Plot:

Above given plot is exactly appearing how I want, but only difficulty is, geom_raster doesn't support ggplotly tooltip on mouseover. Also, few other overlapping of geom_points in case of larger dataset.

That is why, I want to use bubble plot instead of geom_raster. But I am unable to get, how it can be done ? How, I can categorize data in grid format in single plot. ?

Also, is there any way I can put bubbles in more organized way inside a square tile instead of randomly (jittering) plotting which leads to overlapping sometimes.

I am sure there are ways to achieve same result without geom_raster. Please help!

Playing around with ggplot, you can customize it. Unfortunately I don't know a workaround for geom_jitter().

sales_data <- data.frame(
 emp_name = rep(c("Sam", "Dave", "John", "Harry", "Clark", "Kent", "Kenneth", "Richard", "Clement", "Toby", "Jonathan"), times = 3), 
 month = as.factor(rep(c("Jan", "Feb", "Mar", "Jan", "Feb", "Mar", "Jan", "Feb", "Mar", "Jan", "Jan"), times = 3)),
 dept_name = as.factor(rep(c("Production", "Services", "Support", "Support", "Services", "Production", "Production", "Support", "Support", "Support", "Production"), times = 3)), 
 revenue = rep(c(100, 200, 300, 400, 500, 600, 500, 400, 300, 200, 500), times = 3),
 status = rep(c("Low", "Medium", "Medium", "High", "Very High", "Very High", "Very High", "High", "Medium", "Medium", "Low"), times = 3)
)

sales_data$status <- factor(sales_data$status, levels = c("Low", "Medium", "High", "Very High"),ordered = T)
sales_data$month <- factor(sales_data$month, levels = c("Jan", "Feb", "Mar"), ordered = T)


plot = sales_data%>%
 ggplot(aes(x = month, y = dept_name, label = emp_name))+
 geom_jitter(aes(color = revenue),width = 0.3, height = 0.3)+
 geom_vline(xintercept=c(1.5,2.5))+
 geom_hline(yintercept = c(1.5,2.5))+
 theme_bw()+
 theme(panel.grid.major = element_blank(),
 axis.line = element_line(colour = "black"))+
 labs(x = "Month", y = "Department Name")


plotly::ggplotly(plot)

Here we first plot the points, then add our own lines using geom_vline and geom_hline. Then we modify the background.