how to map more than 10 different line types in ggplot2
0
I have to map 11 different line types, trying to use scale_linetype_manual to specify that but unable to do that.
dat <- data.frame(Subject = c(1,1,1,2,2,2,3,3,4,4,4,5,5,5,6,6,6,7,7,7,8,8,8,9,10,10,10,11,11,11),
Time = c("C1D1","C1D8","C2D1","C1D1","C1D8","C2D1","C1D1","C1D8","C1D1","C1D8","C2D1"," C1D1","C1D8","C2D1","C1D1","C1D8","C2D1","C1D1","C1D8","C2D1","C1D1","C1D8","C2D 1","C1D1","C1D1","C1D8","C2D1","C1D1","C1D8","C2D1"),
Response = c("Responder","Responder","Responder","Progressive","Progressive","Progressive", "Non-evaluable","Non-evaluable","Non-evaluable","Non-evaluable","Non- evaluable","Stable","Stable","Stable","Progressive","Progressive","Progressive", "Progressive","Progressive","Progressive","Non-evaluable","Non- evaluable","Non-evaluable","Non-evaluable","Stable","Stable","Stable","Non- evaluable","Non-evaluable","Non-evaluable"),
Eotaxin = c(401.5,463,363.5,332.5,319,212,527.5,421.5,369.5,535,221.5,936.5,1021.5,550.5,4 58.5,386,340,172.5,212.5,160.5,267,301,300.5,300.5,1160,1018,994.5,197,392.5,220 .5)
)
dat$Subject <- as.character(dat$Subject)
nms <- names(dat)
for(biomark in 4:4){
#png(filename = paste("../../../Roswell/plot/",nms[biomark],".png",sep = ""),width = 1500,height = 1000,res = 200)
p <- ggplot() +
geom_line(data = dat, aes(x = dat$Time, y = dat[,biomark],group = dat$Subject, linetype = Subject, colour = Response)) +
labs(title = nms[biomark]) +
scale_linetype_manual(breaks = c("1","2","3","4","5","6","7","8","9","10","11"),
values = c("dotted", "solid", "dashed", "F1", "solid", "solid", "solid", "solid", "solid", "solid", "solid")) +
xlab("Time") +
ylab(nms[biomark]) +
theme_minimal() +
theme(plot.title = element_text(size = 12,face="bold",hjust = 0.5),
axis.title = element_text(size= 12, face = "bold"),
legend.text = element_text(size = 7),
legend.title = element_text(size = 7,face = "bold"),
legend.key.size = unit(0.5, "cm"))
plot(p)
#dev.off()
}
The plot shows that why the line type legends do not match what specified in scale_linetype_manual especially for the first 4 types, the third and fourth types are still solid when I specified "dashed" and "F1"?
resulted plot
r types line
asked Nov 14 '18 at 16:48
dotahuancidotahuanci
63
add a comment |
0
I have to map 11 different line types, trying to use scale_linetype_manual to specify that but unable to do that.
dat <- data.frame(Subject = c(1,1,1,2,2,2,3,3,4,4,4,5,5,5,6,6,6,7,7,7,8,8,8,9,10,10,10,11,11,11),
Time = c("C1D1","C1D8","C2D1","C1D1","C1D8","C2D1","C1D1","C1D8","C1D1","C1D8","C2D1"," C1D1","C1D8","C2D1","C1D1","C1D8","C2D1","C1D1","C1D8","C2D1","C1D1","C1D8","C2D 1","C1D1","C1D1","C1D8","C2D1","C1D1","C1D8","C2D1"),
Response = c("Responder","Responder","Responder","Progressive","Progressive","Progressive", "Non-evaluable","Non-evaluable","Non-evaluable","Non-evaluable","Non- evaluable","Stable","Stable","Stable","Progressive","Progressive","Progressive", "Progressive","Progressive","Progressive","Non-evaluable","Non- evaluable","Non-evaluable","Non-evaluable","Stable","Stable","Stable","Non- evaluable","Non-evaluable","Non-evaluable"),
Eotaxin = c(401.5,463,363.5,332.5,319,212,527.5,421.5,369.5,535,221.5,936.5,1021.5,550.5,4 58.5,386,340,172.5,212.5,160.5,267,301,300.5,300.5,1160,1018,994.5,197,392.5,220 .5)
)
dat$Subject <- as.character(dat$Subject)
nms <- names(dat)
for(biomark in 4:4){
#png(filename = paste("../../../Roswell/plot/",nms[biomark],".png",sep = ""),width = 1500,height = 1000,res = 200)
p <- ggplot() +
geom_line(data = dat, aes(x = dat$Time, y = dat[,biomark],group = dat$Subject, linetype = Subject, colour = Response)) +
labs(title = nms[biomark]) +
scale_linetype_manual(breaks = c("1","2","3","4","5","6","7","8","9","10","11"),
values = c("dotted", "solid", "dashed", "F1", "solid", "solid", "solid", "solid", "solid", "solid", "solid")) +
xlab("Time") +
ylab(nms[biomark]) +
theme_minimal() +
theme(plot.title = element_text(size = 12,face="bold",hjust = 0.5),
axis.title = element_text(size= 12, face = "bold"),
legend.text = element_text(size = 7),
legend.title = element_text(size = 7,face = "bold"),
legend.key.size = unit(0.5, "cm"))
plot(p)
#dev.off()
}
The plot shows that why the line type legends do not match what specified in scale_linetype_manual especially for the first 4 types, the third and fourth types are still solid when I specified "dashed" and "F1"?
resulted plot
r types line
asked Nov 14 '18 at 16:48
dotahuancidotahuanci
63
It's easier to help you if you include a simple reproducible example with sample input and desired output that can be used to test and verify possible solutions. Right now we have no idea what your data actually looks like.
– MrFlick
Nov 14 '18 at 16:54
1
Will this really be a graph that's easy to read? Perhaps using different ggplot syntax meant for differentiating between distributions is more fitting (facet, color etc)?
– 12b345b6b78
Nov 14 '18 at 16:55
2
aes()expects unquoted column names, change toaes(x = Time, y = biomark, group = Subject, linetype = Subject, colour = Response).With those changes all yourlabsshould be set correctly by default. It may help with your linetype problem as well.
– Gregor
Nov 14 '18 at 16:56
sample data is provided, thx @MrFlick
– dotahuanci
Nov 14 '18 at 17:35
add a comment |
0
0
0
I have to map 11 different line types, trying to use scale_linetype_manual to specify that but unable to do that.
dat <- data.frame(Subject = c(1,1,1,2,2,2,3,3,4,4,4,5,5,5,6,6,6,7,7,7,8,8,8,9,10,10,10,11,11,11),
Time = c("C1D1","C1D8","C2D1","C1D1","C1D8","C2D1","C1D1","C1D8","C1D1","C1D8","C2D1"," C1D1","C1D8","C2D1","C1D1","C1D8","C2D1","C1D1","C1D8","C2D1","C1D1","C1D8","C2D 1","C1D1","C1D1","C1D8","C2D1","C1D1","C1D8","C2D1"),
Response = c("Responder","Responder","Responder","Progressive","Progressive","Progressive", "Non-evaluable","Non-evaluable","Non-evaluable","Non-evaluable","Non- evaluable","Stable","Stable","Stable","Progressive","Progressive","Progressive", "Progressive","Progressive","Progressive","Non-evaluable","Non- evaluable","Non-evaluable","Non-evaluable","Stable","Stable","Stable","Non- evaluable","Non-evaluable","Non-evaluable"),
Eotaxin = c(401.5,463,363.5,332.5,319,212,527.5,421.5,369.5,535,221.5,936.5,1021.5,550.5,4 58.5,386,340,172.5,212.5,160.5,267,301,300.5,300.5,1160,1018,994.5,197,392.5,220 .5)
)
dat$Subject <- as.character(dat$Subject)
nms <- names(dat)
for(biomark in 4:4){
#png(filename = paste("../../../Roswell/plot/",nms[biomark],".png",sep = ""),width = 1500,height = 1000,res = 200)
p <- ggplot() +
geom_line(data = dat, aes(x = dat$Time, y = dat[,biomark],group = dat$Subject, linetype = Subject, colour = Response)) +
labs(title = nms[biomark]) +
scale_linetype_manual(breaks = c("1","2","3","4","5","6","7","8","9","10","11"),
values = c("dotted", "solid", "dashed", "F1", "solid", "solid", "solid", "solid", "solid", "solid", "solid")) +
xlab("Time") +
ylab(nms[biomark]) +
theme_minimal() +
theme(plot.title = element_text(size = 12,face="bold",hjust = 0.5),
axis.title = element_text(size= 12, face = "bold"),
legend.text = element_text(size = 7),
legend.title = element_text(size = 7,face = "bold"),
legend.key.size = unit(0.5, "cm"))
plot(p)
#dev.off()
}
The plot shows that why the line type legends do not match what specified in scale_linetype_manual especially for the first 4 types, the third and fourth types are still solid when I specified "dashed" and "F1"?
resulted plot
r types line
asked Nov 14 '18 at 16:48
dotahuancidotahuanci
63
I have to map 11 different line types, trying to use scale_linetype_manual to specify that but unable to do that.
dat <- data.frame(Subject = c(1,1,1,2,2,2,3,3,4,4,4,5,5,5,6,6,6,7,7,7,8,8,8,9,10,10,10,11,11,11),
Time = c("C1D1","C1D8","C2D1","C1D1","C1D8","C2D1","C1D1","C1D8","C1D1","C1D8","C2D1"," C1D1","C1D8","C2D1","C1D1","C1D8","C2D1","C1D1","C1D8","C2D1","C1D1","C1D8","C2D 1","C1D1","C1D1","C1D8","C2D1","C1D1","C1D8","C2D1"),
Response = c("Responder","Responder","Responder","Progressive","Progressive","Progressive", "Non-evaluable","Non-evaluable","Non-evaluable","Non-evaluable","Non- evaluable","Stable","Stable","Stable","Progressive","Progressive","Progressive", "Progressive","Progressive","Progressive","Non-evaluable","Non- evaluable","Non-evaluable","Non-evaluable","Stable","Stable","Stable","Non- evaluable","Non-evaluable","Non-evaluable"),
Eotaxin = c(401.5,463,363.5,332.5,319,212,527.5,421.5,369.5,535,221.5,936.5,1021.5,550.5,4 58.5,386,340,172.5,212.5,160.5,267,301,300.5,300.5,1160,1018,994.5,197,392.5,220 .5)
)
dat$Subject <- as.character(dat$Subject)
nms <- names(dat)
for(biomark in 4:4){
#png(filename = paste("../../../Roswell/plot/",nms[biomark],".png",sep = ""),width = 1500,height = 1000,res = 200)
p <- ggplot() +
geom_line(data = dat, aes(x = dat$Time, y = dat[,biomark],group = dat$Subject, linetype = Subject, colour = Response)) +
labs(title = nms[biomark]) +
scale_linetype_manual(breaks = c("1","2","3","4","5","6","7","8","9","10","11"),
values = c("dotted", "solid", "dashed", "F1", "solid", "solid", "solid", "solid", "solid", "solid", "solid")) +
xlab("Time") +
ylab(nms[biomark]) +
theme_minimal() +
theme(plot.title = element_text(size = 12,face="bold",hjust = 0.5),
axis.title = element_text(size= 12, face = "bold"),
legend.text = element_text(size = 7),
legend.title = element_text(size = 7,face = "bold"),
legend.key.size = unit(0.5, "cm"))
plot(p)
#dev.off()
}
The plot shows that why the line type legends do not match what specified in scale_linetype_manual especially for the first 4 types, the third and fourth types are still solid when I specified "dashed" and "F1"?
resulted plot
r types line
r types line
asked Nov 14 '18 at 16:48
dotahuancidotahuanci
63
asked Nov 14 '18 at 16:48
dotahuancidotahuanci
63
edited Nov 14 '18 at 17:34
dotahuanci
asked Nov 14 '18 at 16:48
dotahuancidotahuanci
63
asked Nov 14 '18 at 16:48
dotahuancidotahuanci
63
asked Nov 14 '18 at 16:48
dotahuancidotahuanci
63
63
It's easier to help you if you include a simple reproducible example with sample input and desired output that can be used to test and verify possible solutions. Right now we have no idea what your data actually looks like.
– MrFlick
Nov 14 '18 at 16:54
1
Will this really be a graph that's easy to read? Perhaps using different ggplot syntax meant for differentiating between distributions is more fitting (facet, color etc)?
– 12b345b6b78
Nov 14 '18 at 16:55
2
aes()expects unquoted column names, change toaes(x = Time, y = biomark, group = Subject, linetype = Subject, colour = Response).With those changes all yourlabsshould be set correctly by default. It may help with your linetype problem as well.
– Gregor
Nov 14 '18 at 16:56
sample data is provided, thx @MrFlick
– dotahuanci
Nov 14 '18 at 17:35
add a comment |
It's easier to help you if you include a simple reproducible example with sample input and desired output that can be used to test and verify possible solutions. Right now we have no idea what your data actually looks like.
– MrFlick
Nov 14 '18 at 16:54
1
Will this really be a graph that's easy to read? Perhaps using different ggplot syntax meant for differentiating between distributions is more fitting (facet, color etc)?
– 12b345b6b78
Nov 14 '18 at 16:55
2
aes()expects unquoted column names, change toaes(x = Time, y = biomark, group = Subject, linetype = Subject, colour = Response).With those changes all yourlabsshould be set correctly by default. It may help with your linetype problem as well.
– Gregor
Nov 14 '18 at 16:56
sample data is provided, thx @MrFlick
– dotahuanci
Nov 14 '18 at 17:35
It's easier to help you if you include a simple reproducible example with sample input and desired output that can be used to test and verify possible solutions. Right now we have no idea what your data actually looks like.
– MrFlick
Nov 14 '18 at 16:54
It's easier to help you if you include a simple reproducible example with sample input and desired output that can be used to test and verify possible solutions. Right now we have no idea what your data actually looks like.
– MrFlick
Nov 14 '18 at 16:54
1
1
Will this really be a graph that's easy to read? Perhaps using different ggplot syntax meant for differentiating between distributions is more fitting (facet, color etc)?
– 12b345b6b78
Nov 14 '18 at 16:55
Will this really be a graph that's easy to read? Perhaps using different ggplot syntax meant for differentiating between distributions is more fitting (facet, color etc)?
– 12b345b6b78
Nov 14 '18 at 16:55
2
2
aes() expects unquoted column names, change to aes(x = Time, y = biomark, group = Subject, linetype = Subject, colour = Response).With those changes all your labs should be set correctly by default. It may help with your linetype problem as well.– Gregor
Nov 14 '18 at 16:56
aes() expects unquoted column names, change to aes(x = Time, y = biomark, group = Subject, linetype = Subject, colour = Response).With those changes all your labs should be set correctly by default. It may help with your linetype problem as well.– Gregor
Nov 14 '18 at 16:56
sample data is provided, thx @MrFlick
– dotahuanci
Nov 14 '18 at 17:35
sample data is provided, thx @MrFlick
– dotahuanci
Nov 14 '18 at 17:35
add a comment |
0
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It's easier to help you if you include a simple reproducible example with sample input and desired output that can be used to test and verify possible solutions. Right now we have no idea what your data actually looks like.
– MrFlick
Nov 14 '18 at 16:54
1
Will this really be a graph that's easy to read? Perhaps using different ggplot syntax meant for differentiating between distributions is more fitting (facet, color etc)?
– 12b345b6b78
Nov 14 '18 at 16:55
2
aes()expects unquoted column names, change toaes(x = Time, y = biomark, group = Subject, linetype = Subject, colour = Response).With those changes all yourlabsshould be set correctly by default. It may help with your linetype problem as well.– Gregor
Nov 14 '18 at 16:56
sample data is provided, thx @MrFlick
– dotahuanci
Nov 14 '18 at 17:35