I am trying to make a single plot using dataset with same X axis but different Y axis. As an example, I have this dataset:
A1 <- rnorm(100)
B1 <- rnorm(100)
B2 <- rnorm(100)
B3 <- rnorm(100)
grid <- matrix(c(1:3),nrow=3,ncol=1,byrow=TRUE)
layout(grid)
plot(A1,B1)
plot(A1,B2)
plot(A1,B3)
This is what I get and comes with multiple X axis:
I know how to do it using ggplot2 but I am looking for another way like using layout. Any help would be much appreciated.
You can
Use the mfcol argument in par to set the number of plots, use mar to leave out the margins, oma to add space to axis which you will make with axis, and mgp to set the space for the axis label you will make.
Make the plots without axis with axes = FALSE.
Use box to add the boxes around the plots.
Add the axis labels in the end with mtext.
Here is an example
set.seed(32273438)
A1 <- rnorm(100)
B1 <- rnorm(100)
B2 <- rnorm(100)
B3 <- rnorm(100)
par(mfcol = c(3, 1), mar = numeric(4), oma = c(4, 4, .5, .5),
mgp = c(2, .6, 0))
plot(A1, B1, axes = FALSE)
axis(2L)
box()
plot(A1, B2, axes = FALSE)
axis(2L)
box()
plot(A1, B3, axes = FALSE)
axis(1L)
axis(2L)
box()
mtext("A1", side = 1, outer = TRUE, line = 2.2)
mtext("B", side = 2, outer = TRUE, line = 2.2)
You may have issues with overlapping y-ticks but you solve this with a the yaxp argument of par.
Its too easy by working with par(mar) and layout function.
par(mar=c(6,6,4,4))
layout(matrix(1:3, ncol = 1), widths = 1, heights = c(2.3,2,2.3), respect = FALSE)
par(mar = c(0, 4.1, 4.1, 2.1))
plot(B1,A1,xaxt='n')
par(mar = c(0, 4.1, 0, 2.1))
plot(B2,A1,xaxt='n')
par(mar = c(4.1, 4.1, 0, 2.1))
plot(B3,A1)
enter image description here
Related
I need to add a "separating" line in Base R boxplot to separate difference groups. In the example below, I want to separate groups A and B (each having 2 levels) using a horizontal line (in red). R codes for reproducible results:
dat = data.frame(A1 = rnorm(1000, 0, 1), A2 = rnorm(1000, 1, 2),
B1 = rnorm(1000, 0.5, 0.5), B2 = rnorm(1000, 1.5, 1.5))
boxplot(dat, horizontal = T, outline=F)
Is there an easy way to do in Base R?
Also, is there an easy way to color the y-axis labels? I want to have A1 and B1 shown as red, and A2 and B2 shown as blue in the axis.
Thanks!
Use abline. To get the right position take the mean of the axTicks of the y-axis.
To get the colored labels, first omit yaxt and rebuild axis ticks and mtext, also using axTicks.
b <- boxplot(dat, horizontal=T, outline=F, yaxt="n")
ats <- axTicks(2)
axis(2, labels=F)
mtext(b$names, 2, 1, col=c(2, 4), at=ats)
abline(h=mean(ats), lwd=2, col=2)
If you want axis tick label colors corresponding to the labels, use segments instead.
b <- boxplot(dat, horizontal=T, outline=F, yaxt="n")
ats <- axTicks(2)
abline(h=mean(ats), lwd=2, col=2)
pu <- par()$usr
Map(function(x, y) segments(pu[1] - .2, x, pu[1], x, xpd=T, col=y), ats, c(2, 4))
mtext(b$names, 2, 1, col=c(2, 4), at=ats)
Edit: To adjust the space a little more use at=option in boxplot and leave out the middle axTicks.
b <- boxplot(dat, horizontal=T, outline=F, yaxt="n", at=c(1, 2, 4, 5))
ats <- axTicks(2)[-3]
abline(h=mean(ats), lwd=2, col=2)
pu <- par()$usr
Map(function(x, y) segments(pu[1] - .2, x, pu[1], x, xpd=T, col=y), ats, c(2, 4))
mtext(b$names, 2, 1, col=c(2, 4), at=ats)
While plotting a boxplot in R, I noticed not all values in the y-axis are presented. Possible values are -5 to 5, but actual values are -1.3 to 4.6, so the values presented on the y-axis are -2 to 5. I want it to be presented with all values: -5 to 5, even though there's no data for this entire range.
My code looks like this:
boxplot(depvar ~ indepvar, data = a, pars = list(outlwd = 2, outcex = 1.8), axes = FALSE)
axis(side = 2, at = seq(-5, 5, by = 1), las = 1, tck = 7)
What should be added/changed for the y-axis to be fully-presented?
Appears simliar to this question: How to set the y range in boxplot graph?
I think you are looking for ylim.
a <- c((randu$x*3)-2)
boxplot(x = a,
ylim = c(-5,5))
Load Packages
install.packages("dplyr")
library(dplyr)
creating random set with two columns:
set.seed(10)
df <- dplyr::data_frame(
x = 1:5,
y = 1:5)
Visualize in a boxplot with expanded axis:
boxplot(x~y,
df,
xlim =c(-5,5),
ylim =c(-5,5))
I am looking for advice for plotting 2 similar wave forms with different y axes scales (one is mmHg and another is m/s) in the same plot. However, I would like to stagger the plots with respect to each other.
For example, using the below:
set.seed(123)
y <- sin(2*pi*x)
g <- sin(2*pi*x)+ rnorm(200, sd=0.1)
plot(y,type="l",
ann = F,
axes = F)
axis(side = 2)
par(new = T)
plot(g,type="l",
ann = F,
axes = F)
axis(side = 4)
Gives:
I would like to achieve something like this (see link below):
How to achieve this?
Here's a slightly cheaty solution:
x <- seq(from = 1, to = 3, by = 0.01)
y <- sin(2*pi*x)
set.seed(123)
g <- sin(2*pi*x)+ rnorm(length(x), sd=0.1)
stagger <- 2
glabels <- c(-1, 0, 1)
plot(c(min(y),max(y)+stagger) ~ c(1,length(y)), type="n", axes=FALSE, ann=FALSE)
lines(y)
axis(side = 2, at = min(y):max(y))
par(new = T)
lines(g+stagger)
axis(side = 4, at = glabels + stagger, labels = glabels)
Results in:
There's probably a better way to generate the positions and labels for the y-axis for g.
I'm trying to tile plots, specifically in a 2x3 matrix, for example:
x <- seq(1, 10, by=.01)
y <- 1/x
prms<-
list(xlab=rep(c("", "x"), each=3),
ylab=rep(c("y", "", ""), 2),
xaxt=rep(c("n", "s"), each=3),
yaxt=rep(c("s", "n", "n"), 2),
mar=list(c(0 , 4.1, 4.1, 0),
c(0 , 0, 4.1, 0),
c(0 , 0, 4.1, 1.1),
c(5.1, 4.1, 0, 0),
c(5.1, 0, 0, 0),
c(5.1, 0, 0, 1.1)))
par(mfrow=c(2, 3))
for (ii in 1:6){
par(mar=prms$mar[[ii]])
plot(x, y, type="l", lwd=2,
xlab=prms$xlab[ii], ylab=prms$lab[ii],
xaxt=prms$xaxt[ii], yaxt=prms$yaxt[ii])
}
Which produces:
I've suppressed the "inner" margins and axes because all x (resp., y) units are the same, so such axes would be redundant. However, as you can see, by squeezing the margins on the left- and rightmost plots, I've accidentally given the middle plots too much space (it's not as apparent, but the same trouble plagues the top vis-a-vis the bottom row).
Therein lies the conundrum. mfrow assigns equal space to each subplot (i.e., axes, margins, etc), not to each plot area. How can I change my approach so that each plotting area is of equal size, ceteris paribus (i.e., axes, etc. unchanged)? I thought of using layout, but couldn't think of a nice programmatic way to go about making sure everything has equal representation.
You may set mar to 0, and use oma to give the size of the outer margins. Axes are added to relevant plots in a loop. Common x and y axis labels are added with mtext and outer = TRUE
par(mfrow = c(2, 3),
mar = c(0, 0, 0, 0),
oma = c(4, 4, 0.5, 0.5))
for (i in 1:6) {
plot(x, y, type = "l", axes = FALSE)
if (i %in% c(4, 5, 6))
axis(side = 1)
if (i %in% c(1, 4))
axis(side = 2)
box()
}
mtext("x values", side = 1, outer = TRUE, line = 2.5)
mtext("y values", side = 2, outer = TRUE, line = 2.5)
See also How to create multiple plots, each with same plot area size, when only one plot has axis labels?
I'd like to do a vertical histogram. Ideally I should be able to put multiple on a single plot per day.
If this could be combined with quantmod experimental chart_Series or some other library capable of drawing bars for a time series that would be great. Please see the attached screenshot. Ideally I could plot something like this.
Is there anything built in or existing libraries that can help with this?
I wrote something a year or so ago to do vertical histograms in base graphics. Here it is, with a usage example.
VerticalHist <- function(x, xscale = NULL, xwidth, hist,
fillCol = "gray80", lineCol = "gray40") {
## x (required) is the x position to draw the histogram
## xscale (optional) is the "height" of the tallest bar (horizontally),
## it has sensible default behavior
## xwidth (required) is the horizontal spacing between histograms
## hist (required) is an object of type "histogram"
## (or a list / df with $breaks and $density)
## fillCol and lineCol... exactly what you think.
binWidth <- hist$breaks[2] - hist$breaks[1]
if (is.null(xscale)) xscale <- xwidth * 0.90 / max(hist$density)
n <- length(hist$density)
x.l <- rep(x, n)
x.r <- x.l + hist$density * xscale
y.b <- hist$breaks[1:n]
y.t <- hist$breaks[2:(n + 1)]
rect(xleft = x.l, ybottom = y.b, xright = x.r, ytop = y.t,
col = fillCol, border = lineCol)
}
## Usage example
require(plyr) ## Just needed for the round_any() in this example
n <- 1000
numberOfHists <- 4
data <- data.frame(ReleaseDOY = rnorm(n, 110, 20),
bin = as.factor(rep(c(1, 2, 3, 4), n / 4)))
binWidth <- 1
binStarts <- c(1, 2, 3, 4)
binMids <- binStarts + binWidth / 2
axisCol <- "gray80"
## Data handling
DOYrange <- range(data$ReleaseDOY)
DOYrange <- c(round_any(DOYrange[1], 15, floor),
round_any(DOYrange[2], 15, ceiling))
## Get the histogram obects
histList <- with(data, tapply(ReleaseDOY, bin, hist, plot = FALSE,
breaks = seq(DOYrange[1], DOYrange[2], by = 5)))
DOYmean <- with(data, tapply(ReleaseDOY, bin, mean))
## Plotting
par(mar = c(5, 5, 1, 1) + .1)
plot(c(0, 5), DOYrange, type = "n",
ann = FALSE, axes = FALSE, xaxs = "i", yaxs = "i")
axis(1, cex.axis = 1.2, col = axisCol)
mtext(side = 1, outer = F, line = 3, "Length at tagging (mm)",
cex = 1.2)
axis(2, cex.axis = 1.2, las = 1, line = -.7, col = "white",
at = c(75, 107, 138, 169),
labels = c("March", "April", "May", "June"), tck = 0)
mtext(side = 2, outer = F, line = 3.5, "Date tagged", cex = 1.2)
box(bty = "L", col = axisCol)
## Gridlines
abline(h = c(60, 92, 123, 154, 184), col = "gray80")
biggestDensity <- max(unlist(lapply(histList, function(h){max(h[[4]])})))
xscale <- binWidth * .9 / biggestDensity
## Plot the histograms
for (lengthBin in 1:numberOfHists) {
VerticalHist(binStarts[lengthBin], xscale = xscale,
xwidth = binWidth, histList[[lengthBin]])
}
Violin plots might be close enough to what you want. They are density plots that have been mirrored through one axis, like a hybrid of a boxplot and a density plot. (Much easier to understanding by example than description. :-) )
Here is a simple (somewhat ugly) example of the ggplot2 implementation of them:
library(ggplot2)
library(lubridate)
data(economics) #sample dataset
# calculate year to group by using lubridate's year function
economics$year<-year(economics$date)
# get a subset
subset<-economics[economics$year>2003&economics$year<2007,]
ggplot(subset,aes(x=date,y=unemploy))+
geom_line()+geom_violin(aes(group=year),alpha=0.5)
A prettier example would be:
ggplot(subset,aes(x=date,y=unemploy))+
geom_violin(aes(group=year,colour=year,fill=year),alpha=0.5,
kernel="rectangular")+ # passes to stat_density, makes violin rectangular
geom_line(size=1.5)+ # make the line (wider than normal)
xlab("Year")+ # label one axis
ylab("Unemployment")+ # label the other
theme_bw()+ # make white background on plot
theme(legend.position = "none") # suppress legend
To include ranges instead of or in addition to the line, you would use geom_linerange or geom_pointrange.
If you use grid graphics then you can create rotated viewports whereever you want them and plot to the rotated viewport. You just need a function that will plot using grid graphics into a specified viewport, I would suggest ggplot2 or possibly lattice for this.
In base graphics you could write your own function to plot the rotated histogram (modify the plot.histogram function or just write your own from scratch using rect or other tools). Then you can use the subplot function from the TeachingDemos package to place the plot wherever you want on a larger plot.