I'm trying to add panel labels to different facets in a plot. I want them to be 1:7, but, the following code
d <- ggplot(diamonds, aes(carat, price, fill = ..density..)) +
xlim(0, 2) + stat_binhex(na.rm = TRUE) + opts(aspect.ratio = 1)
d1<-d + facet_wrap(~ color)
d1+annotate("text", x=0.25, y=1.5e+04, label=1:7)
yields
Error: When _setting_ aesthetics, they may only take one value. Problems: label
Now, I can supply a single value and get that replicated across all facets. But how can I have different labels in different facets using annotate()?
With annotate, you can't. But by setting up a data.frame and using it as the data source for a geom_text, it is easy (with a few bookkeeping aspects).
d1 + geom_text(data=data.frame(x=0.25, y=1.5e+04, label=1:7,
color=c("D","E","F","G","H","I","J")),
aes(x,y,label=label), inherit.aes=FALSE)
Related
I am having a very simple logical problem in ggplot.
Please see the attached graph.
I want multiple lines in each facet, I am getting only one line.
Each set of values need to be connected individually across the Attribute.
The code I have used is :
library(ggplot2)
h <- ggplot(data = df, mapping = aes(Attribute, Values, colour = Classe))
h + geom_point(size = 0.7) + geom_line() + facet_wrap( ~ Classe, scales = "free_x")
I am trying to plot two ´geom_vline()´ in a graph.
The code below works fine for one vertical line:
x=1:7
y=1:7
df1 = data.frame(x=x,y=y)
vertical.lines <- c(2.5)
ggplot(df1,aes(x=x, y=y)) +
geom_line()+
geom_vline(aes(xintercept = vertical.lines))
However, when I add the second desired vertical line by changing
vertical.lines <- c(2.5,4), I get the error:
´Error: Aesthetics must be either length 1 or the same as the data (7): xintercept´
How do I fix that?
Just remove aes() when you use + geom_vline:
ggplot(df1,aes(x=x, y=y)) +
geom_line()+
geom_vline(xintercept = vertical.lines)
It's not working because the second aes() conflicts with the first, it has to do with the grammar of ggplot.
You should see +geom_vline as a layer of annotation to the graph, not like +geom_points or +geom_line which are for mapping data to the plot. (See here how they are in two different sections).
All the aesthetics need to have either length 1 or the same as the data, as the error tells you. But the annotations can have different lengths.
Data:
x=1:7
y=1:7
df1 = data.frame(x=x,y=y)
vertical.lines <- c(2.5,4)
ggplot(df1, aes(x = x, y = y)) +
geom_line() +
sapply(vertical.lines, function(xint) geom_vline(aes(xintercept = xint)))
When I combine geom_vline() with facet_grid() like so:
DATA <- data.frame(x = 1:6,y = 1:6, f = rep(letters[1:2],3))
ggplot(DATA,aes(x = x,y = y)) +
geom_point() +
facet_grid(f~.) +
geom_vline(xintercept = 2:3,
colour =c("goldenrod3","dodgerblue3"))
I get an error message stating Error: Aesthetics must be either length 1 or the same as the data (4): colour because there are two lines in each facet and there are two facets. One way to get around this is to use rep(c("goldenrod3","dodgerblue3"),2), but this requires that every time I change the faceting variables, I also have to calculate the number of facets and replace the magic number (2) in the call to rep(), which makes re-using ggplot code so much less nimble.
Is there a way to get the number of facets directly from ggplot for use in this situation?
You could put the xintercept and colour info into a data.frame to pass to geom_vline and then use scale_color_identity.
ggplot(DATA, aes(x = x, y = y)) +
geom_point() +
facet_grid(f~.) +
geom_vline(data = data.frame(xintercept = 2:3,
colour = c("goldenrod3","dodgerblue3") ),
aes(xintercept = xintercept, color = colour) ) +
scale_color_identity()
This side-steps the issue of figuring out the number of facets, although that could be done by pulling out the number of unique values in the faceting variable with something like length(unique(DATA$f)).
I'm currently working on a very simple data.frame, containing three columns:
x contains x-coordinates of a set of points,
y contains y-coordinates of the set of points, and
weight contains a value associated to each point;
Now, working in ggplot2 I seem to be able to plot contour levels for these data, but i can't manage to find a way to fill the plot according to the variable weight. Here's the code that I used:
ggplot(df, aes(x,y, fill=weight)) +
geom_density_2d() +
coord_fixed(ratio = 1)
You can see that there's no filling whatsoever, sadly.
I've been trying for three days now, and I'm starting to get depressed.
Specifying fill=weight and/or color = weight in the general ggplot call, resulted in nothing. I've tried to use different geoms (tile, raster, polygon...), still nothing. Tried to specify the aes directly into the geom layer, also didn't work.
Tried to convert the object as a ppp but ggplot can't handle them, and also using base-R plotting didn't work. I have honestly no idea of what's wrong!
I'm attaching the first 10 points' data, which is spaced on an irregular grid:
x = c(-0.13397460,-0.31698730,-0.13397460,0.13397460,-0.28867513,-0.13397460,-0.31698730,-0.13397460,-0.28867513,-0.26794919)
y = c(-0.5000000,-0.6830127,-0.5000000,-0.2320508,-0.6547005,-0.5000000,-0.6830127,-0.5000000,-0.6547005,0.0000000)
weight = c(4.799250e-01,5.500250e-01,4.799250e-01,-2.130287e+12,5.798250e-01,4.799250e-01,5.500250e-01,4.799250e-01,5.798250e-01,6.618956e-01)
any advise? The desired output would be something along these lines:
click
Thank you in advance.
From your description geom_density doesn't sound right.
You could try geom_raster:
ggplot(df, aes(x,y, fill = weight)) +
geom_raster() +
coord_fixed(ratio = 1) +
scale_fill_gradientn(colours = rev(rainbow(7)) # colourmap
Here is a second-best using fill=..level... There is a good explanation on ..level.. here.
# load libraries
library(ggplot2)
library(RColorBrewer)
library(ggthemes)
# build your data.frame
df <- data.frame(x=x, y=y, weight=weight)
# build color Palette
myPalette <- colorRampPalette(rev(brewer.pal(11, "Spectral")), space="Lab")
# Plot
ggplot(df, aes(x,y, fill=..level..) ) +
stat_density_2d( bins=11, geom = "polygon") +
scale_fill_gradientn(colours = myPalette(11)) +
theme_minimal() +
coord_fixed(ratio = 1)
I'm mapping size to a variable with something like a log distribution - mostly small values but a few very large ones. How can I make the legend display custom values in the low-value range? For example:
df = data.frame(x=rnorm(2000), y=rnorm(2000), v=abs(rnorm(2000)^5))
p = ggplot(df, aes(x, y)) +
geom_point(aes(col=v, size=v), alpha=0.75) +
scale_size_area(max_size = 10)
print(p)
I've tried p + guides(shape=guide_legend(override.aes=list(size=8))) solution posted in this SO question, but it makes no difference in my plot. In any case I'd like to use specific legend size values e.g. v = c(10,25,50,100,250,500) instead of the default range e.g. c(100,200,300,400)..
Grateful for assistance.
To get different break points of size in legend, modify scale_size_area() by adding argument breaks=. With breaks= you can set breakpoints at positions you need.
ggplot(df, aes(x, y)) +
geom_point(aes(col=v, size=v), alpha=0.75) +
scale_size_area(max_size = 10,breaks=c(10,25,50,100,250,500))