When trying to plot some data in ggplot2 using geom_line(), I noticed that the legend items become empty if I use alpha < 1. How can I fix this and why is this happening?
# dummy data
data <- data.frame(
x = rep(1:10, 10),
y = 1:100 + c(runif(50,0,5), runif(50,0,10)),
grp = c(rep("A", 50), rep("B", 50)))
# using alpha on defaul = 1
ggplot(data, aes(x = x, y = y, col = grp)) +
geom_line()
When I plot the same graph, but with alpha < 1, the lines in the legend completely disappear:
# using alpha < 1
ggplot(data, aes(x = x, y = y, col = grp)) +
geom_line(alpha = 0.9)
(versions: R 4.1.3, ggplot2 3.3.5)
Edit: Updating R and restarting RStudio did not help. This also occurs when using R directly without RStudio.
I ran into the same problem. When saving the plots to PDF/PNG the lines do appear in the legend.
Another workaround I found is adding geom_point() so that way at least you have the colors in the legend:
ggplot(data, aes(x = x, y = y, col = grp)) +
geom_line(alpha = 0.4) +
geom_point(alpha = 0.4, size = 0.1) +
guides(colour = guide_legend(override.aes = list(size=4)))
Legend take the same aes() than plot, you can override this by override.aes.
This should work
ggplot(data, aes(x = x, y = y, col = grp)) +
geom_line(alpha = 0.2) + # using alpha = 0.2 to have it more evident
guides(col = guide_legend(override.aes = list(alpha = 1)))
The same can be used for example to change shape or color of legend elements, respect to aes() mapping in plot
Related
I'm having some issue overlaying 2 point graphs on a box plot. The code seems to work well when i added only one point graph. Here is the code below:
ggplot(data1, aes(x= reorder(DMU,order), y = Efficiency)) +
geom_boxplot() +
geom_point(data = data2, aes(x = dmu, y = eff, color = "eff")) +
scale_color_manual("", breaks = c("eff"), values = c("blue")) +
geom_point(data = data3, aes(x = DMU, y = eff2, color = "eff2")) +
scale_color_manual("", breaks = c("eff2"), values = c("red"))
I keep getting the error below:
Scale for 'colour' is already present. Adding another scale for
'colour', which will replace the existing scale.
Error: Insufficient values in manual scale. 2 needed but only 1 provided.
You cannot add scale_color_manual() twice.
Build a single dataframe for the colon:
df_points <- data.frame(x = c(data2$dmu, data3$DMU),
y = c(data2$eff, data3$eff2),
data = c("data2", "data3")
)
And then:
ggplot(data1, aes(x = reorder(DMU,order), y = Efficiency)) +
geom_boxplot() +
geom_point(data = df_points, aes(x = x, y = y, color = data)) +
scale_colour_manual(values = c("red", "blue") +
theme(legend.position = "none")
Not having the data available I could have made a mistake
The following code block generates a plot with two legends:
Spend7d_bubble <- ggplot(cluster_visuals,
aes(x = ltv_7d, y = avg_daily_sessions,
color = factor(cluster8), size = n)) +
geom_point(alpha = 0.5) +
scale_size_continuous(range = c(2, 25))
Notice how this generates two legends on the right, one for n and one for factor(cluster8).
How can I only include the legend for factor(cluster8) and also rename it to just 'cluster'?
Spend7d_bubble <- ggplot(cluster_visuals,
aes(x = ltv_7d, y = avg_daily_sessions,
color = factor(cluster8), size = n)) +
geom_point(alpha = 0.5) +
scale_size_continuous(range = c(2, 25), guide = 'none') +
labs(color = "Cluster")
Whichever of those aesthetics (color or size) that you don't want a legend for, should be out of aes(). As you see, you don't have any legend for alpha in geom_point since it is not an argument of aes.
ggplot(cluster_visuals,
aes(x = ltv_7d, y = avg_daily_sessions, color = factor(cluster8)), size = n) +
geom_point(alpha = 0.5) +
scale_size_continuous(range = c(2, 25))
I have two sets of data, which I want to present using a heat map with the viridis color scale. For the first data set, my values range from 0 to 1.2 and I can easily see the differences I want to see. However my second data set has some outliers, resulting in a range from 0 to 2. Now it's harder to see the differences in the interesting range between 0 and 1 and it's more diffucult to compare the two images directly. Is there a possibility to show the data from 0 to 1.2 using the viridis colour scale while showing the higher values in yellow ("highest" colour of the viridis scale)?
Here is an example:
library(viridis)
#Create Data
DataSet1 <- expand.grid(x = 0:5, y = 0:5)
DataSet1$z <- runif(36, 0, 1.2)
DataSet2 <- expand.grid(x = 0:5, y = 0:5)
DataSet2$z <- runif(36, 0, 2)
#Plot Data
ggplot(DataSet1, aes(x, y, fill = z)) +
geom_tile() +
scale_fill_viridis() +
geom_text(aes(label = round(z, 2)), size = 2)
DataSet1: Differences between 0.5 and 0.7 are easy to see
ggplot(DataSet2, aes(x, y, fill = z)) +
geom_tile() +
scale_fill_viridis() +
geom_text(aes(label = round(z, 2)), size = 2)
DataSet2: Differences between 0.5 and 0.7 are diffucult to see
EDIT 2022-05-03: The scale function is called scale_fill_viridis_c() these days.
#ClausWilke's solution is better because it shows in the legend, but sometimes one just needs a quick solution without having to write too much specific code. This one also relies on the scales package
ggplot(DataSet2, aes(x, y, fill = z)) +
geom_tile() +
scale_fill_viridis_c(limits = c(0.2, 1), oob = scales::squish) +
geom_text(aes(label = round(z, 2)), size = 2)
You can define an arbitrary rescaling function. Not sure this looks that great, would likely need some work with the legend, but in principle this mechanism allows you to map data values onto the scale in any way you want.
ggplot(DataSet2, aes(x, y, fill = z)) +
geom_tile() +
scale_fill_viridis(rescaler = function(x, to = c(0, 1), from = NULL) {
ifelse(x<1.2,
scales::rescale(x,
to = to,
from = c(min(x, na.rm = TRUE), 1.2)),
1)}) +
geom_text(aes(label = round(z, 2)), size = 2)
Are you looking for something like this?
ggplot(DataSet2, aes(x, y, fill = z)) +
geom_tile() +
scale_fill_gradient(low="green", high="red", limits=c(0, 1.2),
na.value = "yellow") +
geom_text(aes(label = round(z, 2)), size = 2)
Using the viridis colors, asper jazzurro recommendation.
ggplot(DataSet2, aes(x, y, fill = z)) +
geom_tile() +
scale_fill_gradientn(colors = viridis_pal()(9), limits=c(0, 1.2),
na.value = "#FDE725FF") +
geom_text(aes(label = round(z, 2)), size = 2)
It's not necessarily an improvement, but you could do something like this to show the higher values in yellow:
DataSet2A <- DataSet2 %>% filter(z <= 1.2)
DataSet2B <- DataSet2 %>% filter(z > 1.2)
ggplot(DataSet2A, aes(x, y, fill = z)) +
geom_tile() +
scale_fill_viridis(begin = 0, end = .75) +
geom_text(aes(label = round(z, 2)), size = 2) +
geom_tile(data = DataSet2B, aes(x, y), fill = "yellow")
Maybe if you play around with the cutoff as well as the begin= and end= parameters in the scale, which control the portion of the viridis scale that you're employing, you can achieve the result you want. (Note that you can only have one fill scale per plot, but you can set additional constant fills as I've done here with yellow.)
Example data frame (if there's a better/more idiomatic way to do this, let me know):
n <- 10
group <- rep(c("A","B","C"),each = n)
x <- rep(seq(0,1,length = n),3)
y <- ifelse(group == "A",1+x,ifelse(group == "B",2+2*x,3+3*x))
df <- data.frame(group,x,y)
xd <- 0.5
des <- data.frame(xd)
I want to plot create point-line plots for the data in df, add a vertical curve at the x location indicated by xd, and get readable legends for both. I tried the following:
p <- ggplot(data = df, aes(x = x, y = y, color = group)) + geom_point() + geom_line(aes(linetype=group))
p <- p + geom_vline(data = des, aes(xintercept = xd), color = "blue")
p
Not quite what I had in mind, there's no legend for the vertical line.
A small modification (I don't understand why geom_vline is one of the few geometries with a show.legend parameter, which moreover defaults to FALSE!):
p <- ggplot(data = df, aes(x = x, y = y, color = group)) + geom_point() + geom_line(aes(linetype=group))
p <- p + geom_vline(data = des, aes(xintercept = xd), color = "blue", show.legend = TRUE)
p
At least now the vertical bar is showing in the legend, but I don't want it to go in the same "category" (?) as group. I would like another legend entry, titled Design, and containing only the vertical line. How can I achieve this?
A possible approach is to add an extra dummy aesthetic like fill =, which we'll subsequently use to create the second legend in combination with scale_fill_manual() :
ggplot(data = df, aes(x = x, y = y, color = group)) +
geom_point() +
geom_line(aes(linetype=group), show.legend = TRUE) +
geom_vline(data = des,
aes(xintercept = xd, fill = "Vertical Line"), # add dummy fill
colour = "blue") +
scale_fill_manual(values = 1, "Design", # customize second legend
guide = guide_legend(override.aes = list(colour = c("blue"))))
I'm trying to create a scatterplot where the points are jittered (geom_jitter), but I also want to create a black outline around each point. Currently I'm doing it by adding 2 geom_jitters, one for the fill and one for the outline:
beta <- paste("beta == ", "0.15")
ggplot(aes(x=xVar, y = yVar), data = data) +
geom_jitter(size=3, alpha=0.6, colour=my.cols[2]) +
theme_bw() +
geom_abline(intercept = 0.0, slope = 0.145950, size=1) +
geom_vline(xintercept = 0, linetype = "dashed") +
annotate("text", x = 2.5, y = 0.2, label=beta, parse=TRUE, size=5)+
xlim(-1.5,4) +
ylim(-2,2)+
geom_jitter(shape = 1,size = 3,colour = "black")
However, that results in something like this:
Because jitter randomly offsets the data, the 2 geom_jitters are not in line with each other. How do I ensure the outlines are in the same place as the fill points?
I've see threads about this (e.g. Is it possible to jitter two ggplot geoms in the same way?), but they're pretty old and not sure if anything new has been added to ggplot that would solve this issue
The code above works if, instead of using geom_jitter, I use the regular geom_point, but I have too many overlapping points for that to be useful
EDIT:
The solution in the posted answer works. However, it doesn't quite cooperate for some of my other graphs where I'm binning by some other variable and using that to plot different colours:
ggplot(aes(x=xVar, y = yVar, color=group), data = data) +
geom_jitter(size=3, alpha=0.6, shape=21, fill="skyblue") +
theme_bw() +
geom_vline(xintercept = 0, linetype = "dashed") +
scale_colour_brewer(name = "Title", direction = -1, palette = "Set1") +
xlim(-1.5,4) +
ylim(-2,2)
My group variable has 3 levels, and I want to colour each group level by a different colour in the brewer Set1 palette. The current solution just colours everything skyblue. What should I fill by to ensure I'm using the correct colour palette?
You don't actually have to use two layers; you can just use the fill aesthetic of a plotting character with a hole in it:
# some random data
set.seed(47)
df <- data.frame(x = rnorm(100), y = runif(100))
ggplot(aes(x = x, y = y), data = df) + geom_jitter(shape = 21, fill = 'skyblue')
The colour, size, and stroke aesthetics let you customize the exact look.
Edit:
For grouped data, set the fill aesthetic to the grouping variable, and use scale_fill_* functions to set color scales:
# more random data
set.seed(47)
df <- data.frame(x = runif(100), y = rnorm(100), group = sample(letters[1:3], 100, replace = TRUE))
ggplot(aes(x=x, y = y, fill=group), data = df) +
geom_jitter(size=3, alpha=0.6, shape=21) +
theme_bw() +
geom_vline(xintercept = 0, linetype = "dashed") +
scale_fill_brewer(name = "Title", direction = -1, palette = "Set1")