How to color geom_point() circle in R-CodePudding

I have the following data:

dat <- structure(list(station = c(980009L, 980042L, 980145L, 980338L, 
980351L, 980365L, 980563L), JAN = c(0.04, 0.04, 0.04, 0.04, 0.04, 
0.05, 0), FEB = c(0.05, 0.04, 0.99, 0.99, 0.99, 0.04, 0.99), 
 MAR = c(0.04, 0.99, 0.99, 0.99, 0.99, 0.99, 0), APR = c(0.05, 
 0.04, 0.99, 0.99, 0.99, 0.99, 0), MAY = c(0.06, 0.05, 0.95, 
 0.05, 0.96, 0.94, 0.98), JUN = c(0.05, 0.07, 0.04, 0.04, 
 0.05, 0.04, 0.99), JUL = c(0.05, 0.04, 0, 0.93, 0.92, 0.97, 
 0), AUG = c(0.04, 0.06, 0.98, 0.98, 0.99, 0.99, 0), SEP = c(0.04, 
 0.04, 0.98, 0.04, 0.04, 0.04, 0), OCT = c(0.04, 0.07, 0.99, 
 0.05, 0.04, 0.99, 0), NOV = c(0.04, 0.07, 0.99, 0.05, 0.06, 
 0.05, 0), DEC = c(0.04, 0.99, 0.05, 0.04, 0.04, 0.05, 0)), class = "data.frame", 
 row.names = c(NA,-7L))

I want to plot a bubble plot using ggplot. I have the following script:

library(ggplot2)
library(reshape2)
dat<-read.csv("dat.csv",header=T)
dat<-as.data.frame(dat)
pcm<-melt(dat,id = c("station"))

pcm$station<-factor(pcm$station,levels=unique(pcm$station))

p<-ggplot(pcm, aes(x = variable, y = station))
p<-p   geom_point(aes(fill=value*100,size=value*100),alpha = 0.5, shape = 21)
p<-p   coord_fixed(ratio=1)
p<-p   labs( x= "month", y = "station", size = "Percentage", fill ="")

p<-p   scale_size_continuous(limits=c(0,100),breaks=seq(0,100,by=10))
p<-p   scale_x_discrete(expand=c(0.1,0))



png("Bubble_plot.png")
print(p)
dev.off()

Here's the output.

Questions:

a). How can I add colors to the circles? I want to remove the color bar and color the circles.

b). I am also having a problem changing the color into 10 discrete colors. I want to use viridis() here. Any suggestions on how to do this correctly in R?

link to viridis color: https://www.datanovia.com/en/blog/top-r-color-palettes-to-know-for-great-data-visualization/

I'll appreciate any help on this.

CodePudding user response：

To combine legends for two scales you must do two things:

Use guide_legend() as the guide for both scales (already default for size).
Ensure all name, breaks, labels, limits, etc. parameters match between the scales.

To use discrete colours from the viridis package for a continuous scale you can use the binned colour/fill scale scale_{colour/fill}_viridis_b().

# dat <- structure(...) # omitted for brevity
  
library(ggplot2)
library(reshape2)
dat<-as.data.frame(dat)
pcm<-melt(dat,id = c("station"))

pcm$station<-factor(pcm$station,levels=unique(pcm$station))

ggplot(pcm, aes(x = variable, y = station))   
  geom_point(aes(fill=value*100,size=value*100),alpha = 0.5, shape = 21)   
  coord_fixed(ratio=1)  
  labs( x= "month", y = "station", size = "Percentage", fill ="Percentage")  
  scale_size_continuous(limits=c(0,100),breaks=seq(0,100,by=10))  
  scale_fill_viridis_b(limits = c(0, 100), breaks = seq(0, 100, by = 10),
                        guide = guide_legend())  
  scale_x_discrete(expand=c(0.1,0))