I have a 4x4 geom_tile plot where the upper right cell contains an additional 4x4 cell. I am wanting the plot to appear as it does below.
The positions are listed inside the cells for clarity, however, the code makes the data value corresponding with the position placed in the cell. The sample code I provided currently produces this:
I am not able to manipulate the data values in terms of position (values for x and y cannot be changed) and the cell containing additional breakdown will not always be in the upper right so a solution that does not hardcode this location in would be appreciated.
If this is possible I would greatly appreciate any assistance you can provide!
x <- c(0,0,1,0.5,0.5,1,1)
y <- c(0,1,0,0.5,1,0.5,1)
data_val <- sample(0:100, 7)
alldata <-data.frame(x, y, data_val)
ggplot(data= alldata, aes(x, y)) +
geom_tile(colour = "black") +
geom_text(aes(label = data_val),colour="white")
This requires a slight change to your notation, so that x and y correctly locate the centre of each square, and an additional width parameter (which with this system really only depends on whether x and y are even or odd). For other quartered squares, use -1/+1 instead of 3/5 as appropriate.
x <- c(0,0,4,3,3,5,5)
y <- c(0,4,0,3,5,3,5)
w <- ifelse(x%%2==0, 4, 2)
data_val <- sample(0:100, 7)
alldata <- data.frame(x, y, w, data_val)
ggplot(data= alldata, aes(x=x, y=y, width=w, height=w)) +
geom_tile(fill = "white", color="black") +
geom_text(aes(label = data_val), colour="black") +
coord_fixed()
Related
For some unfortunate technical reasons, I need to have a pixel plot.
For example, let's take this simple plot:
plot(0,0)
Points(x=1:10, y=rep(0,10), cex=1)
I need each dot to be exactly a pixel wide. The size parameter cex does not seem to allow such precision.
You could use ggplot with the option geom_point(shape = ".").
For example
# generate random dataframe
df <- data.frame(x = runif(100), y = runif(100))
# make the figure
ggplot(df) + aes(x = x, y = y) + geom_point(shape = ".") + theme_void()
This will create something like:
I've created a plot in ggplot2 and then "on top" of that plot I have used geom_rect() to visualize (in red) the data points with the lowest 10% of values of z. I would still like to use scale_fill_gradientn to fill the legend/scale bar, but I would like to insert the color red at the minimum of the fill (i.e. that bottom of the vertical scale). How can I use scale_fill_gradientn and do this? Or, how can I achieve the desired result using another method?
# The example code here produces an plot for illustrative purposes only.
# create data frame, from ggplot2 documentation
df <- expand.grid(x = 0:5, y = 0:5)
df$z <- runif(nrow(df))
# select min. 10%
df.1 <- df[df$z <= quantile(df$z, 0.1),]
#plot
ggplot(df, aes(x, y, fill = z)) + geom_raster() +
scale_fill_gradientn(colours=topo.colors(7),na.value = "transparent") +
geom_rect(data=df.1, size=1, fill="red", colour=NA , aes(xmin=x-.5, xmax=x+.5, ymin=y-.5, ymax=y+.5))
One solution would be provide "red" as one of the colors in scale_fill_gradientn(). Red is used twice to ensure that in range from 0 to 0.1 all values get "red" then with seq() all other values in range from 0.1001 to 1 are distributed evenly. In this case you don't need a second dataframe.
set.seed(123)
df <- expand.grid(x = 0:5, y = 0:5)
df$z <- runif(nrow(df))
ggplot(df, aes(x, y, fill = z)) + geom_raster() +
scale_fill_gradientn(colours=c("red","red",topo.colors(6)),
values=c(0,0.1,seq(0.1001,1,length.out=7)),na.value = "transparent")
I would like to change the line size with a continuous variable. Now I used the geom_line with aesthetics size. For example:
x <- 1:100
y <- x * x
z <- abs(cos(x * pi / (max(x))))
df <- data.frame(x = x, y = y, z = z)
library(ggplot2)
ggplot(df, aes(x, y, size = z)) + geom_line()
But there are some spaces among segments (see figure below. Please zoom in to see the spaces). it seems ggplot2 uses rectangles to plot each segment.
I have increased the point number, but spaces till exist for bigger curvature.
My question is how to remove these spaces. I really appreciate it for any suggestions.
Adjust the multiplier to your preference:
mult <- 200
ggplot(df, aes(x, y)) + geom_line() + geom_ribbon(aes(ymin=y-mult*z, ymax=y+mult*z))
I am trying to make a labeled bubble plot with ggplot2 in R. Here is the simplified scenario:
I have a data frame with 4 variables: 3 quantitative variables, x, y, and z, and another variable that labels the points, lab.
I want to make a scatter plot, where the position is determined by x and y, and the size of the points is determined by z. I then want to place text labels beside the points (say, to the right of the point) without overlapping the text on top of the point.
If the points did not vary in size, I could try to simply modify the aesthetic of the geom_text layer by adding a scaling constant (e.g. aes(x=x+1, y=y+1)). However, even in this simple case, I am having a problem with positioning the text correctly because the points do not scale with the output dimensions of the plot. In other words, the size of the points remains constant in a 500x500 plot and a 1000x1000 plot - they do not scale up with the dimensions of the outputted plot.
Therefore, I think I have to scale the position of the label by the size (e.g. dimensions) of the output plot, or I have to get the radius of the points from ggplot somehow and shift my text labels. Is there a way to do this in ggplot2?
Here is some code:
# Stupid data
df <- data.frame(x=c(1,2,3),
y=c(1,2,3),
z=c(1,2,1),
lab=c("a","b","c"), stringsAsFactors=FALSE)
# Plot with bad label placement
ggplot(aes(x=x, y=y), data=df) +
geom_point(aes(size=z)) +
geom_text(aes(label=lab),
colour="red") +
scale_size_continuous(range=c(5, 50), guide="none")
EDIT: I should mention, I tried hjust and vjust inside of geom_text, but it does not produce the desired effect.
# Trying hjust and vjust, but it doesn't look nice
ggplot(aes(x=x, y=y), data=df) +
geom_point(aes(size=z)) +
geom_text(aes(label=lab), hjust=0, vjust=0.5,
colour="red") +
scale_size_continuous(range=c(5, 50), guide="none")
EDIT: I managed to get something that works for now, thanks to Henrik and shujaa. I will leave the question open just in case someone shares a more general solution.
Just a blurb of what I am using this for: I am plotting a map, and indicating the amount of precipitation at certain stations with a point that is sized proportionally to the amount of precipitation observed. I wanted to add a station label beside each point in an aesthetically pleasing manner. I will be making more of these plots for different regions, and my output plot may have a different resolution or scale (e.g. due to different projections) for each plot, so a general solution is desired. I might try my hand at creating a custom position_jitter, like baptiste suggested, if I have time during the weekend.
It appears that position_*** don't have access to the scales used by other layers, so it's a no go. You could make a clone of GeomText that shifts the labels according to the size mapped,
but it's a lot of effort for a very kludgy and fragile solution,
geom_shiftedtext <- function (mapping = NULL, data = NULL, stat = "identity",
position = "identity",
parse = FALSE, ...) {
GeomShiftedtext$new(mapping = mapping, data = data, stat = stat, position = position,
parse = parse, ...)
}
require(proto)
GeomShiftedtext <- proto(ggplot2:::GeomText, {
objname <- "shiftedtext"
draw <- function(., data, scales, coordinates, ..., parse = FALSE, na.rm = FALSE) {
data <- remove_missing(data, na.rm,
c("x", "y", "label"), name = "geom_shiftedtext")
lab <- data$label
if (parse) {
lab <- parse(text = lab)
}
with(coord_transform(coordinates, data, scales),
textGrob(lab, unit(x, "native") + unit(0.375* size, "mm"),
unit(y, "native"),
hjust=hjust, vjust=vjust, rot=angle,
gp = gpar(col = alpha(colour, alpha),
fontfamily = family, fontface = fontface, lineheight = lineheight))
)
}
})
df <- data.frame(x=c(1,2,3),
y=c(1,2,3),
z=c(1.2,2,1),
lab=c("a","b","c"), stringsAsFactors=FALSE)
ggplot(aes(x=x, y=y), data=df) +
geom_point(aes(size=z), shape=1) +
geom_shiftedtext(aes(label=lab, size=z),
hjust=0, colour="red") +
scale_size_continuous(range=c(5, 100), guide="none")
This isn't a very general solution, because you'll need to tweak it every time, but you should be able to add to the x value for the text some value that's linear depending on z.
I had luck with
ggplot(aes(x=x, y=y), data=df) +
geom_point(aes(size=z)) +
geom_text(aes(label=lab, x = x + .06 + .14 * (z - min(z))),
colour="red") +
scale_size_continuous(range=c(5, 50), guide="none")
but, as the font size depends on your window size, you would need to decide on your output size and tweak accordingly. I started with x = x + .05 + 0 * (z-min(z)) and calibrated the intercept based on the smallest point, then when I was happy with that I adjusted the linear term for the biggest point.
Another alternative. Looks OK with your test data, but you need to check how general it is.
dodge <- abs(scale(df$z))/4
ggplot(data = df, aes(x = x, y = y)) +
geom_point(aes(size = z)) +
geom_text(aes(x = x + dodge), label = df$lab, colour = "red") +
scale_size_continuous(range = c(5, 50), guide = "none")
Update
Just tried position_jitter, but the width argument only takes one value, so right now I am not sure how useful that function would be. But I would be happy to find that I am wrong. Example with another small data set:
df3 <- mtcars[1:10, ]
ggplot(data = df3, aes(x = wt, y = mpg)) +
geom_point(aes(size = qsec), alpha = 0.1) +
geom_text(label = df3$carb, position = position_jitter(width = 0.1, height = 0)) +
scale_size_continuous(range = c(5, 50), guide = "none")
I've become quite fond of boxplots in which jittered points are overlain over the boxplots to represent the actual data, as below:
set.seed(7)
l1 <- gl(3, 1, length=102, labels=letters[1:3])
l2 <- gl(2, 51, length=102, labels=LETTERS[1:2]) # Will use this later
y <- runif(102)
d <- data.frame(l1, l2, y)
ggplot(d, aes(x=l1, y=y)) +
geom_point(position=position_jitter(width=0.2), alpha=0.5) +
geom_boxplot(fill=NA)
(These are particularly helpful when there are very different numbers of data points in each box.)
I'd like to use this technique when I am also (implicitly) using position_dodge to separate boxplots by a second variable, e.g.
ggplot(d, aes(x=l1, y=y, colour=l2)) +
geom_point(position=position_jitter(width=0.2), alpha=0.5) +
geom_boxplot(fill=NA)
However, I can't figure out how to dodge the points by the colour variable (here, l2) and also jitter them.
Here is an approach that manually performs the jittering and dodging.
# a plot with no dodging or jittering of the points
dp <- ggplot(d, aes(x=l1, y=y, colour=l2)) +
geom_point(alpha=0.5) +
geom_boxplot(fill=NA)
# build the plot for rendering
foo <- ggplot_build(dp)
# now replace the 'x' values in the data for layer 1 (unjittered and un-dodged points)
# with the appropriately dodged and jittered points
foo$data[[1]][['x']] <- jitter(foo$data[[2]][['x']][foo$data[[1]][['group']]],amount = 0.2)
# now draw the plot (need to explicitly load grid package)
library(grid)
grid.draw(ggplot_gtable(foo))
# note the following works without explicitly loading grid
plot(ggplot_gtable(foo))
I don't think you'll like it, but I've never found a way around this except to produce your own x values for the points. In this case:
d$l1.num <- as.numeric(d$l1)
d$l2.num <- (as.numeric(d$l2)/3)-(1/3 + 1/6)
d$x <- d$l1.num + d$l2.num
ggplot(d, aes(l1, y, colour = l2)) + geom_boxplot(fill = NA) +
geom_point(aes(x = x), position = position_jitter(width = 0.15), alpha = 0.5) + theme_bw()
It's certainly a long way from ideal, but becomes routine pretty quickly. If anyone has an alternative solution, I'd be very happy!
The new position_jitterdodge() works for this. However, it requires the fill aesthetic to tell it how to group points, so you have to specify a manual fill to get uncolored boxes:
ggplot(d, aes(x=l1, y=y, colour=l2, fill=l2)) +
geom_point(position=position_jitterdodge(width=0.2), alpha=0.5) +
geom_boxplot() + scale_fill_manual(values=rep('white', length(unique(l2))))
I'm using a newer version of ggplot2 (ggplot2_2.2.1.9000) and I was struggling to find an answer that worked for a similar plot of my own. #John Didon's answer produced an error for me; Error in position_jitterdodge(width = 0.2) : unused argument (width = 0.2). I had previous code that worked with geom_jitter that stopped working after downloading the newer version of ggplot2. This is how I solved it below - minimal-fuss code....
ggplot(d, aes(x=l1, y=y, colour=l2, fill=l2)) +
geom_point(position = position_jitterdodge(dodge.width = 1,
jitter.width = 0.5), alpha=0.5) +
geom_boxplot(position = position_dodge(width = 1), fill = NA)
Another option would be to use facets:
set.seed(7)
l1 <- gl(3, 1, length=102, labels=letters[1:3])
l2 <- gl(2, 51, length=102, labels=LETTERS[1:2]) # Will use this later
y <- runif(102)
d <- data.frame(l1, l2, y)
ggplot(d, aes(x=l1, y=y, colour=l2)) +
geom_point(position=position_jitter(width=0.2), alpha=0.5) +
geom_boxplot(fill=NA) +
facet_grid(.~l2) +
theme_bw()
Sorry, don´t have enough points to post the resulting graph.