ggplot2: Combining group, color and linetype
up vote
8
down vote
favorite
I have a data base with 3 factors (condition, measure and time) and would like to plot them using the x-axis, the color/group and the linetype.
As an exemple, my data looks like this:
DT <- data.frame(condition = rep(c("control", "experimental"), each = 4),
measure = rep(c("A", "A", "B", "B"), 2),
time = rep(c("pre-test", "post-test"), 4),
score = 1:8)
> DT
condition measure time score
1 control A pre-test 1
2 control A post-test 2
3 control B pre-test 3
4 control B post-test 4
5 experimental A pre-test 5
6 experimental A post-test 6
7 experimental B pre-test 7
8 experimental B post-test 8
My goal is to draw a graph like this:
I tried:
ggplot(DT, aes(time, score, group = measure, color = measure, linetype = condition)) +
geom_line() +
geom_point()
But it returns this error:
Error: geom_path: If you are using dotted or dashed lines, colour, size and linetype must be constant over the line
What am I missing?
r ggplot2
asked Dec 2 at 15:36
mat
514730
add a comment |
up vote
8
down vote
favorite
I have a data base with 3 factors (condition, measure and time) and would like to plot them using the x-axis, the color/group and the linetype.
As an exemple, my data looks like this:
DT <- data.frame(condition = rep(c("control", "experimental"), each = 4),
measure = rep(c("A", "A", "B", "B"), 2),
time = rep(c("pre-test", "post-test"), 4),
score = 1:8)
> DT
condition measure time score
1 control A pre-test 1
2 control A post-test 2
3 control B pre-test 3
4 control B post-test 4
5 experimental A pre-test 5
6 experimental A post-test 6
7 experimental B pre-test 7
8 experimental B post-test 8
My goal is to draw a graph like this:
I tried:
ggplot(DT, aes(time, score, group = measure, color = measure, linetype = condition)) +
geom_line() +
geom_point()
But it returns this error:
Error: geom_path: If you are using dotted or dashed lines, colour, size and linetype must be constant over the line
What am I missing?
r ggplot2
asked Dec 2 at 15:36
mat
514730
add a comment |
up vote
8
down vote
favorite
up vote
8
down vote
favorite
I have a data base with 3 factors (condition, measure and time) and would like to plot them using the x-axis, the color/group and the linetype.
As an exemple, my data looks like this:
DT <- data.frame(condition = rep(c("control", "experimental"), each = 4),
measure = rep(c("A", "A", "B", "B"), 2),
time = rep(c("pre-test", "post-test"), 4),
score = 1:8)
> DT
condition measure time score
1 control A pre-test 1
2 control A post-test 2
3 control B pre-test 3
4 control B post-test 4
5 experimental A pre-test 5
6 experimental A post-test 6
7 experimental B pre-test 7
8 experimental B post-test 8
My goal is to draw a graph like this:
I tried:
ggplot(DT, aes(time, score, group = measure, color = measure, linetype = condition)) +
geom_line() +
geom_point()
But it returns this error:
Error: geom_path: If you are using dotted or dashed lines, colour, size and linetype must be constant over the line
What am I missing?
r ggplot2
asked Dec 2 at 15:36
mat
514730
I have a data base with 3 factors (condition, measure and time) and would like to plot them using the x-axis, the color/group and the linetype.
As an exemple, my data looks like this:
DT <- data.frame(condition = rep(c("control", "experimental"), each = 4),
measure = rep(c("A", "A", "B", "B"), 2),
time = rep(c("pre-test", "post-test"), 4),
score = 1:8)
> DT
condition measure time score
1 control A pre-test 1
2 control A post-test 2
3 control B pre-test 3
4 control B post-test 4
5 experimental A pre-test 5
6 experimental A post-test 6
7 experimental B pre-test 7
8 experimental B post-test 8
My goal is to draw a graph like this:
I tried:
ggplot(DT, aes(time, score, group = measure, color = measure, linetype = condition)) +
geom_line() +
geom_point()
But it returns this error:
Error: geom_path: If you are using dotted or dashed lines, colour, size and linetype must be constant over the line
What am I missing?
r ggplot2
r ggplot2
asked Dec 2 at 15:36
mat
514730
asked Dec 2 at 15:36
mat
514730
edited Dec 2 at 16:08
asked Dec 2 at 15:36
mat
514730
asked Dec 2 at 15:36
mat
514730
asked Dec 2 at 15:36
mat
514730
514730
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
up vote
7
down vote
accepted
You want to use
ggplot(DT, aes(time, score, group = interaction(measure, condition),
color = measure, linetype = condition)) +
geom_line() + geom_point()
because the actual grouping is not only by measure but also by condition. When grouping by measure alone, I guess it's asking for kind of parallelograms rather than lines.
answered Dec 2 at 15:49
Julius Vainora
30.5k75878
add a comment |
up vote
4
down vote
data.frame(
condition = rep(c("control", "experimental"), each = 4),
measure = rep(c("A", "A", "B", "B"), 2),
time = rep(c("pre-test", "post-test"), 4),
score = 1:8
) -> DT
DT_wide <- tidyr::spread(DT, time, score)
ggplot() +
geom_segment(
data = DT_wide,
aes(
x = "pre-test", xend = "post-test",
y = `pre-test`, yend = `post-test`,
color = measure,
linetype = condition
)
) +
geom_point(
data = DT,
aes(time, score, color = measure)
)
answered Dec 2 at 15:49
hrbrmstr
59.8k685146
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
7
down vote
accepted
You want to use
ggplot(DT, aes(time, score, group = interaction(measure, condition),
color = measure, linetype = condition)) +
geom_line() + geom_point()
because the actual grouping is not only by measure but also by condition. When grouping by measure alone, I guess it's asking for kind of parallelograms rather than lines.
answered Dec 2 at 15:49
Julius Vainora
30.5k75878
add a comment |
up vote
7
down vote
accepted
You want to use
ggplot(DT, aes(time, score, group = interaction(measure, condition),
color = measure, linetype = condition)) +
geom_line() + geom_point()
because the actual grouping is not only by measure but also by condition. When grouping by measure alone, I guess it's asking for kind of parallelograms rather than lines.
answered Dec 2 at 15:49
Julius Vainora
30.5k75878
add a comment |
up vote
7
down vote
accepted
up vote
7
down vote
accepted
You want to use
ggplot(DT, aes(time, score, group = interaction(measure, condition),
color = measure, linetype = condition)) +
geom_line() + geom_point()
because the actual grouping is not only by measure but also by condition. When grouping by measure alone, I guess it's asking for kind of parallelograms rather than lines.
answered Dec 2 at 15:49
Julius Vainora
30.5k75878
You want to use
ggplot(DT, aes(time, score, group = interaction(measure, condition),
color = measure, linetype = condition)) +
geom_line() + geom_point()
because the actual grouping is not only by measure but also by condition. When grouping by measure alone, I guess it's asking for kind of parallelograms rather than lines.
answered Dec 2 at 15:49
Julius Vainora
30.5k75878
answered Dec 2 at 15:49
Julius Vainora
30.5k75878
answered Dec 2 at 15:49
Julius Vainora
30.5k75878
answered Dec 2 at 15:49
Julius Vainora
30.5k75878
30.5k75878
add a comment |
add a comment |
up vote
4
down vote
data.frame(
condition = rep(c("control", "experimental"), each = 4),
measure = rep(c("A", "A", "B", "B"), 2),
time = rep(c("pre-test", "post-test"), 4),
score = 1:8
) -> DT
DT_wide <- tidyr::spread(DT, time, score)
ggplot() +
geom_segment(
data = DT_wide,
aes(
x = "pre-test", xend = "post-test",
y = `pre-test`, yend = `post-test`,
color = measure,
linetype = condition
)
) +
geom_point(
data = DT,
aes(time, score, color = measure)
)
answered Dec 2 at 15:49
hrbrmstr
59.8k685146
add a comment |
up vote
4
down vote
data.frame(
condition = rep(c("control", "experimental"), each = 4),
measure = rep(c("A", "A", "B", "B"), 2),
time = rep(c("pre-test", "post-test"), 4),
score = 1:8
) -> DT
DT_wide <- tidyr::spread(DT, time, score)
ggplot() +
geom_segment(
data = DT_wide,
aes(
x = "pre-test", xend = "post-test",
y = `pre-test`, yend = `post-test`,
color = measure,
linetype = condition
)
) +
geom_point(
data = DT,
aes(time, score, color = measure)
)
answered Dec 2 at 15:49
hrbrmstr
59.8k685146
add a comment |
up vote
4
down vote
up vote
4
down vote
data.frame(
condition = rep(c("control", "experimental"), each = 4),
measure = rep(c("A", "A", "B", "B"), 2),
time = rep(c("pre-test", "post-test"), 4),
score = 1:8
) -> DT
DT_wide <- tidyr::spread(DT, time, score)
ggplot() +
geom_segment(
data = DT_wide,
aes(
x = "pre-test", xend = "post-test",
y = `pre-test`, yend = `post-test`,
color = measure,
linetype = condition
)
) +
geom_point(
data = DT,
aes(time, score, color = measure)
)
answered Dec 2 at 15:49
hrbrmstr
59.8k685146
data.frame(
condition = rep(c("control", "experimental"), each = 4),
measure = rep(c("A", "A", "B", "B"), 2),
time = rep(c("pre-test", "post-test"), 4),
score = 1:8
) -> DT
DT_wide <- tidyr::spread(DT, time, score)
ggplot() +
geom_segment(
data = DT_wide,
aes(
x = "pre-test", xend = "post-test",
y = `pre-test`, yend = `post-test`,
color = measure,
linetype = condition
)
) +
geom_point(
data = DT,
aes(time, score, color = measure)
)
answered Dec 2 at 15:49
hrbrmstr
59.8k685146
answered Dec 2 at 15:49
hrbrmstr
59.8k685146
answered Dec 2 at 15:49
hrbrmstr
59.8k685146
answered Dec 2 at 15:49
hrbrmstr
59.8k685146
59.8k685146
add a comment |
add a comment |
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