Mixing
ggplot lineplot for multiple rows of data - ggplot equivalent for matplot
I am trying to create a plot with a line for each sample which has 24 measured values (i.e. data to be plotted are in rows rather than columns). An example of my data looks like this:
structure(c("23.96000", "25.92000", "20.13000", "20.39000", "13.88000",
"14.97000", "11.56000", "12.75000", " 8.86000", "10.33000", " 8.96000",
" 9.87000", " 7.540000", " 8.160000", " 6.670000", " 7.430000",
" 7.060000", " 7.040000", " 6.250000", " 7.200000", " 6.400000",
" 6.380000", " 6.70000", " 6.05000", " 5.590000", " 6.310000",
" 6.000000", " 5.770000"), .Dim = c(2L, 14L), .Dimnames = list(
NULL, c("La", "Ce", "Pr", "Nd", "Sm", "Eu", "Gd", "Tb", "Dy",
"Ho", "Er", "Tm", "Yb", "Lu")))
I have succeeded in creating the plot I want in matplot with the following code:
m <- as.matrix(data)
REE <- c('La','Ce','Pr','Nd','Sm','Eu','Gd','Tb','Dy','Ho','Er','Tm','Yb','Lu')
m2 <- m[,11:24]
#Plotting with matplot
matplot(t(m2), type = "l", log="y", xaxt ="n",ylab="C/C_Chondrite",ylim=c(1,100))
axis(1, at=1:length(REE), labels=REE)
Which generates:
[REE plot][1]
I have tried the method described in this example: ggplot equivalent for matplot with only using geom_point() just to test out the function,
however I am currently getting a plot like this:
[bad plot][1]
Is anyone able to help?
r matplotlib ggplot2
edited Nov 21 '18 at 21:26
jay.sf
5,26221639
asked Nov 21 '18 at 18:18
lmmlmm
84
add a comment |
I am trying to create a plot with a line for each sample which has 24 measured values (i.e. data to be plotted are in rows rather than columns). An example of my data looks like this:
structure(c("23.96000", "25.92000", "20.13000", "20.39000", "13.88000",
"14.97000", "11.56000", "12.75000", " 8.86000", "10.33000", " 8.96000",
" 9.87000", " 7.540000", " 8.160000", " 6.670000", " 7.430000",
" 7.060000", " 7.040000", " 6.250000", " 7.200000", " 6.400000",
" 6.380000", " 6.70000", " 6.05000", " 5.590000", " 6.310000",
" 6.000000", " 5.770000"), .Dim = c(2L, 14L), .Dimnames = list(
NULL, c("La", "Ce", "Pr", "Nd", "Sm", "Eu", "Gd", "Tb", "Dy",
"Ho", "Er", "Tm", "Yb", "Lu")))
I have succeeded in creating the plot I want in matplot with the following code:
m <- as.matrix(data)
REE <- c('La','Ce','Pr','Nd','Sm','Eu','Gd','Tb','Dy','Ho','Er','Tm','Yb','Lu')
m2 <- m[,11:24]
#Plotting with matplot
matplot(t(m2), type = "l", log="y", xaxt ="n",ylab="C/C_Chondrite",ylim=c(1,100))
axis(1, at=1:length(REE), labels=REE)
Which generates:
[REE plot][1]
I have tried the method described in this example: ggplot equivalent for matplot with only using geom_point() just to test out the function,
however I am currently getting a plot like this:
[bad plot][1]
Is anyone able to help?
r matplotlib ggplot2
edited Nov 21 '18 at 21:26
jay.sf
5,26221639
asked Nov 21 '18 at 18:18
lmmlmm
84
Hi & welcome to Stack Overflow! Please provide yourdatawithdput(data)to make a MCVE. Thanks!
– jay.sf
Nov 21 '18 at 18:20
ggplotis powerful when you feed it long data, but unwieldy with wide data. I suggest you add a step before ggplot where you convert it, e.g.tidyr::gather(element, value, La:Lu)...
– Jon Spring
Nov 21 '18 at 19:16
1
Hi @jay.sf I have changed this - thanks for the tip!
– lmm
Nov 21 '18 at 21:11
@jay.sf I just saw it - thank you!
– lmm
Nov 22 '18 at 14:33
add a comment |
I am trying to create a plot with a line for each sample which has 24 measured values (i.e. data to be plotted are in rows rather than columns). An example of my data looks like this:
structure(c("23.96000", "25.92000", "20.13000", "20.39000", "13.88000",
"14.97000", "11.56000", "12.75000", " 8.86000", "10.33000", " 8.96000",
" 9.87000", " 7.540000", " 8.160000", " 6.670000", " 7.430000",
" 7.060000", " 7.040000", " 6.250000", " 7.200000", " 6.400000",
" 6.380000", " 6.70000", " 6.05000", " 5.590000", " 6.310000",
" 6.000000", " 5.770000"), .Dim = c(2L, 14L), .Dimnames = list(
NULL, c("La", "Ce", "Pr", "Nd", "Sm", "Eu", "Gd", "Tb", "Dy",
"Ho", "Er", "Tm", "Yb", "Lu")))
I have succeeded in creating the plot I want in matplot with the following code:
m <- as.matrix(data)
REE <- c('La','Ce','Pr','Nd','Sm','Eu','Gd','Tb','Dy','Ho','Er','Tm','Yb','Lu')
m2 <- m[,11:24]
#Plotting with matplot
matplot(t(m2), type = "l", log="y", xaxt ="n",ylab="C/C_Chondrite",ylim=c(1,100))
axis(1, at=1:length(REE), labels=REE)
Which generates:
[REE plot][1]
I have tried the method described in this example: ggplot equivalent for matplot with only using geom_point() just to test out the function,
however I am currently getting a plot like this:
[bad plot][1]
Is anyone able to help?
r matplotlib ggplot2
edited Nov 21 '18 at 21:26
jay.sf
5,26221639
asked Nov 21 '18 at 18:18
lmmlmm
84
I am trying to create a plot with a line for each sample which has 24 measured values (i.e. data to be plotted are in rows rather than columns). An example of my data looks like this:
structure(c("23.96000", "25.92000", "20.13000", "20.39000", "13.88000",
"14.97000", "11.56000", "12.75000", " 8.86000", "10.33000", " 8.96000",
" 9.87000", " 7.540000", " 8.160000", " 6.670000", " 7.430000",
" 7.060000", " 7.040000", " 6.250000", " 7.200000", " 6.400000",
" 6.380000", " 6.70000", " 6.05000", " 5.590000", " 6.310000",
" 6.000000", " 5.770000"), .Dim = c(2L, 14L), .Dimnames = list(
NULL, c("La", "Ce", "Pr", "Nd", "Sm", "Eu", "Gd", "Tb", "Dy",
"Ho", "Er", "Tm", "Yb", "Lu")))
I have succeeded in creating the plot I want in matplot with the following code:
m <- as.matrix(data)
REE <- c('La','Ce','Pr','Nd','Sm','Eu','Gd','Tb','Dy','Ho','Er','Tm','Yb','Lu')
m2 <- m[,11:24]
#Plotting with matplot
matplot(t(m2), type = "l", log="y", xaxt ="n",ylab="C/C_Chondrite",ylim=c(1,100))
axis(1, at=1:length(REE), labels=REE)
Which generates:
[REE plot][1]
I have tried the method described in this example: ggplot equivalent for matplot with only using geom_point() just to test out the function,
however I am currently getting a plot like this:
[bad plot][1]
Is anyone able to help?
r matplotlib ggplot2
r matplotlib ggplot2
edited Nov 21 '18 at 21:26
jay.sf
5,26221639
asked Nov 21 '18 at 18:18
lmmlmm
84
edited Nov 21 '18 at 21:26
jay.sf
5,26221639
asked Nov 21 '18 at 18:18
lmmlmm
84
edited Nov 21 '18 at 21:26
jay.sf
5,26221639
edited Nov 21 '18 at 21:26
jay.sf
5,26221639
edited Nov 21 '18 at 21:26
jay.sf
5,26221639
5,26221639
asked Nov 21 '18 at 18:18
lmmlmm
84
asked Nov 21 '18 at 18:18
lmmlmm
84
asked Nov 21 '18 at 18:18
lmmlmm
84
84
Hi & welcome to Stack Overflow! Please provide yourdatawithdput(data)to make a MCVE. Thanks!
– jay.sf
Nov 21 '18 at 18:20
ggplotis powerful when you feed it long data, but unwieldy with wide data. I suggest you add a step before ggplot where you convert it, e.g.tidyr::gather(element, value, La:Lu)...
– Jon Spring
Nov 21 '18 at 19:16
1
Hi @jay.sf I have changed this - thanks for the tip!
– lmm
Nov 21 '18 at 21:11
@jay.sf I just saw it - thank you!
– lmm
Nov 22 '18 at 14:33
add a comment |
Hi & welcome to Stack Overflow! Please provide yourdatawithdput(data)to make a MCVE. Thanks!
– jay.sf
Nov 21 '18 at 18:20
ggplotis powerful when you feed it long data, but unwieldy with wide data. I suggest you add a step before ggplot where you convert it, e.g.tidyr::gather(element, value, La:Lu)...
– Jon Spring
Nov 21 '18 at 19:16
1
Hi @jay.sf I have changed this - thanks for the tip!
– lmm
Nov 21 '18 at 21:11
@jay.sf I just saw it - thank you!
– lmm
Nov 22 '18 at 14:33
Hi & welcome to Stack Overflow! Please provide your
data withdput(data) to make a MCVE. Thanks!– jay.sf
Nov 21 '18 at 18:20
Hi & welcome to Stack Overflow! Please provide your
data withdput(data) to make a MCVE. Thanks!– jay.sf
Nov 21 '18 at 18:20
ggplot is powerful when you feed it long data, but unwieldy with wide data. I suggest you add a step before ggplot where you convert it, e.g. tidyr::gather(element, value, La:Lu)...– Jon Spring
Nov 21 '18 at 19:16
ggplot is powerful when you feed it long data, but unwieldy with wide data. I suggest you add a step before ggplot where you convert it, e.g. tidyr::gather(element, value, La:Lu)...– Jon Spring
Nov 21 '18 at 19:16
1
1
Hi @jay.sf I have changed this - thanks for the tip!
– lmm
Nov 21 '18 at 21:11
Hi @jay.sf I have changed this - thanks for the tip!
– lmm
Nov 21 '18 at 21:11
@jay.sf I just saw it - thank you!
– lmm
Nov 22 '18 at 14:33
@jay.sf I just saw it - thank you!
– lmm
Nov 22 '18 at 14:33
add a comment |
1 Answer
1
active
oldest
votes
You probably need to transpose your data, which is different in your example compared to the linked example.
data <- as.data.frame(t(data)) # transpose your data here with `t()`
data$id <- 1:nrow(data)
library(reshape2)
plot_data <- melt(data,id.var="id")
library(ggplot2)
ggplot(plot_data, aes(x=id, y=value, group=variable, colour=variable)) +
geom_point() +
geom_line(aes(lty=variable))
Yields
answered Nov 21 '18 at 21:21
jay.sfjay.sf
5,26221639
1
Thank you!! This has worked perfectly.
– lmm
Nov 22 '18 at 14:33
add a comment |
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1 Answer
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1 Answer
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active
oldest
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oldest
votes
You probably need to transpose your data, which is different in your example compared to the linked example.
data <- as.data.frame(t(data)) # transpose your data here with `t()`
data$id <- 1:nrow(data)
library(reshape2)
plot_data <- melt(data,id.var="id")
library(ggplot2)
ggplot(plot_data, aes(x=id, y=value, group=variable, colour=variable)) +
geom_point() +
geom_line(aes(lty=variable))
Yields
answered Nov 21 '18 at 21:21
jay.sfjay.sf
5,26221639
1
Thank you!! This has worked perfectly.
– lmm
Nov 22 '18 at 14:33
add a comment |
You probably need to transpose your data, which is different in your example compared to the linked example.
data <- as.data.frame(t(data)) # transpose your data here with `t()`
data$id <- 1:nrow(data)
library(reshape2)
plot_data <- melt(data,id.var="id")
library(ggplot2)
ggplot(plot_data, aes(x=id, y=value, group=variable, colour=variable)) +
geom_point() +
geom_line(aes(lty=variable))
Yields
answered Nov 21 '18 at 21:21
jay.sfjay.sf
5,26221639
1
Thank you!! This has worked perfectly.
– lmm
Nov 22 '18 at 14:33
add a comment |
You probably need to transpose your data, which is different in your example compared to the linked example.
data <- as.data.frame(t(data)) # transpose your data here with `t()`
data$id <- 1:nrow(data)
library(reshape2)
plot_data <- melt(data,id.var="id")
library(ggplot2)
ggplot(plot_data, aes(x=id, y=value, group=variable, colour=variable)) +
geom_point() +
geom_line(aes(lty=variable))
Yields
answered Nov 21 '18 at 21:21
jay.sfjay.sf
5,26221639
You probably need to transpose your data, which is different in your example compared to the linked example.
data <- as.data.frame(t(data)) # transpose your data here with `t()`
data$id <- 1:nrow(data)
library(reshape2)
plot_data <- melt(data,id.var="id")
library(ggplot2)
ggplot(plot_data, aes(x=id, y=value, group=variable, colour=variable)) +
geom_point() +
geom_line(aes(lty=variable))
Yields
answered Nov 21 '18 at 21:21
jay.sfjay.sf
5,26221639
answered Nov 21 '18 at 21:21
jay.sfjay.sf
5,26221639
answered Nov 21 '18 at 21:21
jay.sfjay.sf
5,26221639
answered Nov 21 '18 at 21:21
jay.sfjay.sf
5,26221639
5,26221639
1
Thank you!! This has worked perfectly.
– lmm
Nov 22 '18 at 14:33
add a comment |
1
Thank you!! This has worked perfectly.
– lmm
Nov 22 '18 at 14:33
1
1
Thank you!! This has worked perfectly.
– lmm
Nov 22 '18 at 14:33
Thank you!! This has worked perfectly.
– lmm
Nov 22 '18 at 14:33
add a comment |
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Hi & welcome to Stack Overflow! Please provide your
datawithdput(data)to make a MCVE. Thanks!– jay.sf
Nov 21 '18 at 18:20
ggplotis powerful when you feed it long data, but unwieldy with wide data. I suggest you add a step before ggplot where you convert it, e.g.tidyr::gather(element, value, La:Lu)...– Jon Spring
Nov 21 '18 at 19:16
1
Hi @jay.sf I have changed this - thanks for the tip!
– lmm
Nov 21 '18 at 21:11
@jay.sf I just saw it - thank you!
– lmm
Nov 22 '18 at 14:33