I want to change the background inside guides geometry (those in gray that are signaled by the red arrows)
library(ggplot2)
dat <- data.frame(x = 1:5, y = 1:5, p = 1:5, q = factor(1:5),
r = factor(1:5))
p <- ggplot(dat, aes(x, y, colour = p, size = q, shape = r)) + geom_point()
p
ggplot(dat, aes(x, y, colour = p, size = q, shape = r)) +
geom_point() +
theme(legend.key = element_rect(fill = "green"))
Related
How can I change the black facet labels (A and B) into the color of factors (A and B) red and blue respectively ? There are plenty of examples on how to change the background label colour but not the text color.
library(data.table)
A = data.table(x = 1:4, y = 1:4, z = c('A','A','B','B'))
ggplot(A) + geom_point(aes(x = x, y = y, color = z)) + facet_grid(~z) + theme_bw()
One option to achieve your desired result would be via the ggtext package which via element_markdown allows to style theme elements via HTML, CSS and markdown:
library(ggplot2)
library(ggtext)
cols <- data.frame(
z = c("A", "B"),
color = scales::hue_pal()(2)
)
A <- merge(A, cols, by = "z", all.x = TRUE)
A$facet <- paste0("<span style='color: ", A$color, "'>", A$z, "</span>")
ggplot(A) +
geom_point(aes(x = x, y = y, color = z)) +
facet_grid(~facet) +
theme_bw() +
theme(strip.text.x = ggtext::element_markdown(face = "bold"))
I have made the graph below with ggplot. I would like to reduce the distance between the y axis and the first category (a). Which function should I use? Thanks! :)
library(ggplot2)
library(reshape2)
data <- data.frame(a = rnorm(10), b = rnorm(10), c = rnorm(10), group = 1:10)
data <- melt(data, id = "group")
ggplot(data, aes(x = variable, y = value, group = group, color = as.factor(group))) + geom_point() + geom_line() + theme_minimal() + theme(axis.line = element_line(), panel.grid = element_blank())
Suppose we have the following plot:
library(ggplot2)
df <- data.frame(x = rep(LETTERS[1:3], 3),
y = rnorm(9),
z = rep(letters[1:3], each = 3))
ggplot(df, aes(x, y, colour = z, group = z)) +
geom_line() +
geom_point()
We can reduce the space between the extreme points and the panel edges by adjusting the expand argument in a scale function:
ggplot(df, aes(x, y, colour = z, group = z)) +
geom_line() +
geom_point() +
scale_x_discrete(expand = c(0,0.1))
Setting expand = c(0,0) completely removes the space. The first argument is a relative number, the second an absolute; so in the example above we set the expand to 0.1 x-axis units.
I first make a plot
df <- data.frame(x = c(1:40, rep(1:20, 3), 15:40))
p <- ggplot(df, aes(x=x, y = x)) +
stat_density2d(aes(fill='red',alpha=..level..),geom='polygon', show.legend = F)
Then I want to change the geom_density values and use these in another plot.
# build plot
q <- ggplot_build(p)
# Change density
dens <- q$data[[1]]
dens$y <- dens$y - dens$x
Build the other plot using the changed densities, something like this:
# Built another plot
ggplot(df, aes(x=x, y =1)) +
geom_point(alpha = 0.3) +
geom_density2d(dens)
This does not work however is there a way of doing this?
EDIT: doing it when there are multiple groups:
df <- data.frame(x = c(1:40, rep(1:20, 3), 15:40), group = c(rep('A',40), rep('B',60), rep('C',26)))
p <- ggplot(df, aes(x=x, y = x)) +
stat_density2d(aes(fill=group,alpha=..level..),geom='polygon', show.legend = F)
q <- ggplot_build(p)
dens <- q$data[[1]]
dens$y <- dens$y - dens$x
ggplot(df, aes(x=x, y =1)) +
geom_point(aes(col = group), alpha = 0.3) +
geom_polygon(data = dens, aes(x, y, fill = fill, group = piece, alpha = alpha)) +
scale_alpha_identity() +
guides(fill = F, alpha = F)
Results when applied to my own dataset
Although this is exactly what I'm looking for the fill colors seem not to correspond to the initial colors (linked to A, B and C):
Like this? It is possible to plot a transformation of the shapes plotted by geom_density. But that's not quite the same as manipulating the underlying density...
ggplot(df, aes(x=x, y =1)) +
geom_point(alpha = 0.3) +
geom_polygon(data = dens, aes(x, y, fill = fill, group = piece, alpha = alpha)) +
scale_alpha_identity() +
guides(fill = F, alpha = F)
Edit - OP now has multiple groups. We can plot those with the code below, which produces an artistic plot of questionably utility. It does what you propose, but I would suggest it would be more fruitful to transform the underlying data and summarize that, if you are looking for representative output.
ggplot(df, aes(x=x, y =1)) +
geom_point(aes(col = group), alpha = 0.3) +
geom_polygon(data = dens, aes(x, y, fill = group, group = piece, alpha = alpha)) +
scale_alpha_identity() +
guides(fill = F, alpha = F) +
theme_minimal()
I would like to plot two lines on one chart, one with a color gradient and the other a solid color. I can add individual lines and a gradient:
x <- seq(1, 100, 1)
y <- rnorm(100, 50, 15)
z <- rnorm(100, 30, 5)
df <- data.frame(x,y,z)
library(ggplot2)
ggplot(df, aes(x = x, y = y, color = x)) + geom_line() +
scale_color_gradient(low = "blue", high = "red") +
geom_line(data = df, aes(x = x, y = z, color = x))
But changing the color throws an error:
> ggplot(df, aes(x = x, y = y, color = ..y..)) + geom_line() +
+ scale_color_gradient(low = "blue", high = "red") +
+ geom_line(aes(x = x, y = z, color = "yellow"))
Error: Discrete value supplied to continuous scale
I'm hoping to add labels, but that may be to complex for this...
Simplest way is to specify color for a solid line outside of aes:
library(ggplot2)
ggplot(df, aes(x, y, color = x)) +
geom_line() +
# No need to respecify data or x at it's defined in main ggplot call
geom_line(aes(y = z), color = "yellow") +
scale_color_gradient(low = "blue", high = "red")
I'm plotting 11 curves and the program bellow works well. BUT I'm not able two change the wild colors to plot 11 black curves:
library(ggplot2)
#library(latex2exp)
library(reshape)
fn <- "img/plot.eps"
fct1 <- function(x0 ){
return(1/sin(x0)+1/tan(x0))
}
fct2 <- function(beta, t ){
return(2*atan(exp(t)/beta))
}
t<-seq(from=0,to=10,by=0.01)
s1<-cbind(t, fct2(fct1(-pi+0.0001),t),
fct2(fct1(-1.5),t),
fct2(fct1(-0.5),t),
fct2(fct1(-0.05),t),
fct2(fct1(-0.01),t),
fct2(fct1(0),t),
fct2(fct1(0.01),t),
fct2(fct1(0.05),t),
fct2(fct1(0.5),t),
fct2(fct1(1.5),t),
fct2(fct1(pi),t))
colnames(s1)<-c("time","y1","y2","y3","y4","y5","y6","y7","y8","y9","y10","y11")
s2 <- melt(as.data.frame(s1), id = "time")
q <- ggplot(s2, aes(x = time, y = value, color = variable))
q <- q + geom_line() + ylab("y") + xlab("t")+ ylab("x(t)")+
theme_bw(base_size = 7) + guides(colour = FALSE)
ggsave(file = fn, width = 2, height = 1)
q
EDIT Now the code should be reproducible
You need to map the variable to the grouping, and it will produce black lines by default.
q <- ggplot() +
geom_line(data = s2, aes(x = time, y = value,
group = variable)) +
xlab("t")+ ylab("x(t)") +
theme_bw(base_size = 7) + guides(colour = FALSE)
q
To be perfectly clear, it is possible to map the color to the variable, which can produce black lines, but not without changing the legend. Here is how you would amend the colors after the fact, if you wanted to, having already mapped the color to the variable.
q <- ggplot() +
geom_line(data = s2, aes(x = time, y = value,
color = variable)) +
xlab("t")+ ylab("x(t)") +
theme_bw(base_size = 7) + guides(colour = FALSE) +
scale_color_manual(values = rep("black",11))
q