There are different data sets as bottom.
1-1.Data Set(cidf_min.csv)
name |
number |
value |
samples |
conf |
lower |
upper |
level |
apple |
1 |
0.056008 |
100 |
0.95 |
0.05458 |
0.059141 |
2 |
apple |
2 |
0.048256 |
100 |
0.95 |
0.046363 |
0.059142 |
2 |
apple |
3 |
0.042819 |
100 |
0.95 |
0.040164 |
0.059143 |
2 |
apple |
4 |
0.038663 |
100 |
0.95 |
0.035155 |
0.059144 |
2 |
apple |
5 |
0.035325 |
100 |
0.95 |
0.030146 |
0.059145 |
2 |
1-2.Data Set(newdf_min.csv)
name |
number |
value |
samples |
conf |
lower |
upper |
level |
max |
apple |
2 |
0.01854 |
100 |
0.95 |
-0.06963 |
0.045235 |
2 |
2 |
'''code'''
cidf<-read.csv("D:/cidf_min.csv")
newdf<-read.csv("D:/newdf_min.csv")
p_min<-ggplot(cidf, aes(x=number, y=value, group=name))+geom_line(aes(color=level))+geom_ribbon(aes(ymin=lower, ymax=upper, fill=level, group=name), alpha=0.3)+geom_text(data=newdf, aes(label=name, color=level), hjust=-0.2, vjust=0.5, size=3, show.legend=F)+coord_cartesian(xlim=c(0,max(cidf$number)*1.2))+xlab(~"Con (\u00D7"~C[max]*")")+ylab(~"score ("*mu*"C/"*mu*"F)")+theme_bw()
2-1.Data Set(cidf_max.csv)
name |
number |
value |
samples |
conf |
lower |
upper |
level |
apple |
1 |
0.068832 |
100 |
0.95 |
0.061945 |
0.069416 |
2 |
apple |
2 |
0.065256 |
100 |
0.95 |
0.053687 |
0.065841 |
2 |
apple |
3 |
0.060492 |
100 |
0.95 |
0.046201 |
0.06155 |
2 |
apple |
4 |
0.05585 |
100 |
0.95 |
0.039848 |
0.058739 |
2 |
apple |
5 |
0.047585 |
100 |
0.95 |
0.033555 |
0.056066 |
2 |
2-2.Data Set(newdf_max.csv)
name |
number |
value |
samples |
conf |
lower |
upper |
level |
max |
apple |
2 |
0.024221 |
100 |
0.95 |
-0.04546 |
0.076362 |
2 |
2 |
'''code'''
cidf<-read.csv("D:/cidf_max.csv")
newdf<-read.csv("D:/newdf_max.csv")
p_max<-ggplot(cidf, aes(x=number, y=value, group=name))+geom_line(aes(color=level))+geom_ribbon(aes(ymin=lower, ymax=upper, fill=level, group=name), alpha=0.3)+geom_text(data=newdf, aes(label=name, color=level), hjust=-0.2, vjust=0.5, size=3, show.legend=F)+coord_cartesian(xlim=c(0,max(cidf$number)*1.2))+xlab(~"Con (\u00D7"~C[max]*")")+ylab(~"score ("*mu*"C/"*mu*"F)")+theme_bw()
3-1.Data Set(cidf_mean.csv)
name |
number |
value |
samples |
conf |
lower |
upper |
level |
apple |
1 |
0.069673 |
100 |
0.95 |
0.069673 |
0.069673 |
2 |
apple |
2 |
0.06133 |
100 |
0.95 |
0.057955 |
0.062792 |
2 |
apple |
3 |
0.060497 |
100 |
0.95 |
0.046201 |
0.06155 |
2 |
apple |
4 |
0.054623 |
100 |
0.95 |
0.044241 |
0.058739 |
2 |
apple |
5 |
0.039852 |
100 |
0.95 |
0.031906 |
0.043719 |
2 |
3-2.Data Set(newdf_mean.csv)
name |
number |
value |
samples |
conf |
lower |
upper |
level |
max |
apple |
2 |
0.014323 |
100 |
0.95 |
-0.06793 |
0.045717 |
2 |
2 |
'''code'''
cidf<-read.csv("D:/cidf_mean.csv")
newdf<-read.csv("D:/newdf_mean.csv")
p_mean<-ggplot(cidf, aes(x=number, y=value, group=name))+geom_line(aes(color=level))+geom_ribbon(aes(ymin=lower, ymax=upper, fill=level, group=name), alpha=0.3)+geom_text(data=newdf, aes(label=name, color=level), hjust=-0.2, vjust=0.5, size=3, show.legend=F)+coord_cartesian(xlim=c(0,max(cidf$number)*1.2))+xlab(~"Con (\u00D7"~C[max]*")")+ylab(~"score ("*mu*"C/"*mu*"F)")+theme_bw()
I already drew 3 plots using code of ggplot
, geom_line
and geom_ribbon
etc.
I want to merge plots of p_min
, p_max
and p_mean
.
p_min
, p_max
and p_mean
must locate in y axis.
x axis is number(1,2,3,4,5).
Let me know how to draw plots of multiple y axis using complex variables in a layout.