How to plot a second y axis for one category in the data?-CodePudding

I have this data:

xVal = c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15)
a = c(0.18340368127959822, 0.17496531617798133, 0.16772886654445848, 0.15934821062512169, 
0.15390913489444036, 0.14578798884106348, 0.14524174121702108, 0.13958093302847951, 
0.1365009715515553, 0.13337340345559975, 0.12995175856952607, 0.12583603207983862, 
0.12180656145228715, 0.11824179486798418, 0.11524630600365712)
b = c(0.13544353787855531, 0.11345498050033079, 0.11449834060237293, 0.10479213576778054, 
0.09677430524414686, 0.091990671548439179, 0.089965934807318487, 0.088711600335474206, 
0.088923403079789909, 0.087989321310275717, 0.085424600757017272, 0.08251334730889931, 
0.080178280060313953, 0.077717041621392688, 0.076638743116633837)
c = c(0.087351324973658093, 0.12113308515702567, 0.11422800742900453, 0.11264309199970789, 
0.11390287790920843, 0.10774426268894192, 0.10587704437111881, 0.10474954948318291, 
0.10568277685778472, 0.10201545270338952, 0.09939827283775747, 0.098062403381144761, 
0.094110034623398231, 0.091211408116407641, 0.089369778116029489)
c=c*100
library(ggplot2)
library(reshape2)
df = data.frame(xVal, a, b, c)
df.melt = melt(df, id="xVal")

I can plot it easily

 ggplot(data=df.melt, aes(x=xVal, y=value, colour=variable))  
        geom_point()   
        geom_line()   
        xlab("xVal")   ylab("YValues")   xlim(1,16)

I need to add a secondary y-axis for c

CodePudding user response：

The way to think about a secondary axis is that it is just an annotation. The actual data you are plotting needs to be transformed so it fits in the same scale as the rest of your data.

In your case, this means you need to divide all the c values by 100 to plot them, and draw a secondary axis that is transformed to show numbers 100 times larger:

ggplot(within(df.melt, value[variable == 'c'] <- value[variable == 'c']/100),
  aes(xVal, value, colour = variable))  
  geom_point()   
  geom_line()  
  scale_y_continuous(sec.axis = sec_axis(~.x*100, name = "Values (c)"))

CodePudding user response：

It hink the best way to do this is to create a scaling factor which is applied to the second geom and right y-axis.

Sample code:

library(ggplot2)
library(ggpubr)

  ggplot(data=df.melt, aes(x=xVal, y=value, colour=variable))  
  geom_point(size=2)   
  geom_line(lwd=1)   
  xlab("xVal")   
  ylab("YValues")   
  xlim(1,16)  
  theme_cleveland() 
  scale_y_continuous(sec.axis = sec_axis(~., name = "secondary",
                                         labels = c(8.7351324973658093, 12.113308515702567, 11.422800742900453, 11.264309199970789, 
                                                    11.390287790920843, 10.774426268894192, 10.587704437111881, 10.474954948318291, 
                                                    10.568277685778472, 10.201545270338952, 9.939827283775747, 9.8062403381144761, 
                                                  9.4110034623398231, 9.1211408116407641, 8.9369778116029489),
                                         breaks=c(8.7351324973658093, 12.113308515702567, 11.422800742900453, 11.264309199970789, 
                                                  11.390287790920843, 10.774426268894192, 10.587704437111881, 10.474954948318291, 
                                                  10.568277685778472, 10.201545270338952, 9.939827283775747, 9.8062403381144761, 
                                                  9.4110034623398231, 9.1211408116407641, 8.9369778116029489)) )

Plot:

You could improve the second axis by removing some of the values.

Sample code:

ggplot(data=df.melt, aes(x=xVal, y=value, colour=variable))  
  geom_point(size=2)   
  geom_line(lwd=1)   
  xlab("xVal")   
  ylab("YValues")   
  xlim(1,16)  
  theme_cleveland() 
  scale_y_continuous(sec.axis = sec_axis(~., name = "secondary",
                                         labels = c(8.7351324973658093, 12.113308515702567, 
                                                    11.422800742900453, 10.774426268894192,   
                                                    10.201545270338952,  9.8062403381144761, 
                                                    9.4110034623398231, 9.1211408116407641),
                                         breaks=c(8.7351324973658093, 12.113308515702567, 
                                                  11.422800742900453, 10.774426268894192,   
                                                  10.201545270338952,  9.8062403381144761, 
                                                  9.4110034623398231, 9.1211408116407641) )) 
  theme(
    axis.text.y.left = element_text(color = "blue"),
    axis.text.y.right = element_text(color = "red", size=8),
  )

Plot:

Sample data:

xVal = c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15)
a = c(0.18340368127959822, 0.17496531617798133, 0.16772886654445848, 0.15934821062512169, 
      0.15390913489444036, 0.14578798884106348, 0.14524174121702108, 0.13958093302847951, 
      0.1365009715515553, 0.13337340345559975, 0.12995175856952607, 0.12583603207983862, 
      0.12180656145228715, 0.11824179486798418, 0.11524630600365712)
b = c(0.13544353787855531, 0.11345498050033079, 0.11449834060237293, 0.10479213576778054, 
      0.09677430524414686, 0.091990671548439179, 0.089965934807318487, 0.088711600335474206, 
      0.088923403079789909, 0.087989321310275717, 0.085424600757017272, 0.08251334730889931, 
      0.080178280060313953, 0.077717041621392688, 0.076638743116633837)
c = c(0.087351324973658093, 0.12113308515702567, 0.11422800742900453, 0.11264309199970789, 
      0.11390287790920843, 0.10774426268894192, 0.10587704437111881, 0.10474954948318291, 
      0.10568277685778472, 0.10201545270338952, 0.09939827283775747, 0.098062403381144761, 
      0.094110034623398231, 0.091211408116407641, 0.089369778116029489)
c=c*100