Related
This is my first time using RStudio, and I've tried to find the the answer to my solution along with tinkering around with the code but I haven't been able to figure it out. I've even looked here and found other users with the same issue How to display all x labels in R barplot? and Rotating x axis labels in R for barplot but I wasn't able to get the answered solutions to work for my code. I've also asked two people more familiar with R, but after looking over my code and trying for themselves they were also unable to figure it out as well.
Everything would just result in error messages (I don't have the error messages showing in my console since when someone was trying to figure it out they cleared the global environment).
I have already generated 15 bars for my barplot, and the barplot itself is generated with the labels for the ylab, the title for my xlab, and the main, and I even have it colored, but I can't name each individual column bar.
The names for all the labels are listed in the source, but it's only showing every third bar or so. I need all bars labeled.
setwd("C:/Users/Person/Desktop/Rfolder")
library(readxl)
data <- read_excel("filename.xlsx")
View(topic)
barplot(data$'per hundred',
main ="Title",
xlab = "Words",
ylab = "variable stats",
col = c("gray"))
axis(1, at =c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15),
srt = 45,
labels=c("Apple","Butter","Banana","Bacon","Candy","Carrot","Spam","Ube","Ice cream","Italian ice","Jackfruit","Kale","Tofu","Udon","All types"))
Coded Food Barplot
Use las=2 to set labels from horizontal to vertical.
This one works, with working example added:
df <- cbind.data.frame("names" = c("Apple","Butter","Banana","Bacon","Candy","Carrot","Spam","Ube","Ice cream","Italian ice","Jackfruit","Kale","Tofu","Udon","All types"), "numbers" = sample(20:100, 15))
barplot(height = df$numbers,
names.arg = df$names,
main = "Title",
xlab = "Words",
ylim = c(0, 100),
ylab = "variable stats",
col = c("gray"),
las = 2)
To modify sizing of x axis names and labels, add options:
cex.names = 1 # controls magnification of x axis names. value starts at 1
cex.lab = 1 # control magnification of x & y axis labels. value starts at 1
to the barplot() function. Play around with sizing to find what works for you best. To escape the overlap of x axis label and x axis names, instead of xlab = "Words" use sub = "Words". Simple & efficient.
Here's the barplot generated with all the labels.
Food Labeled Barplot
I have data that is mostly centered in a small range (1-10) but there is a significant number of points (say, 10%) which are in (10-1000). I would like to plot a histogram for this data that will focus on (1-10) but will also show the (10-1000) data. Something like a log-scale for th histogram.
Yes, i know this means not all bins are of equal size
A simple hist(x) gives
while hist(x,breaks=c(0,1,1.1,1.2,1.3,1.4,1.5,1.6,1.7,1.8,1.9,2,3,4,5,7.5,10,15,20,50,100,200,500,1000,10000))) gives
none of which is what I want.
update
following the answers here I now produce something that is almost exactly what I want (I went with a continuous plot instead of bar-histogram):
breaks <- c(0,1,1.1,1.2,1.3,1.4,1.5,1.6,1.7,1.8,1.9,2,4,8)
ggplot(t,aes(x)) + geom_histogram(colour="darkblue", size=1, fill="blue") + scale_x_log10('true size/predicted size', breaks = breaks, labels = breaks)![alt text][3]
the only problem is that I'd like to match between the scale and the actual bars plotted. There two options for doing that : the one is simply use the actual margins of the plotted bars (how?) then get "ugly" x-axis labels like 1.1754,1.2985 etc. The other, which I prefer, is to control the actual bins margins used so they will match the breaks.
Log scale histograms are easier with ggplot than with base graphics. Try something like
library(ggplot2)
dfr <- data.frame(x = rlnorm(100, sdlog = 3))
ggplot(dfr, aes(x)) + geom_histogram() + scale_x_log10()
If you are desperate for base graphics, you need to plot a log-scale histogram without axes, then manually add the axes afterwards.
h <- hist(log10(dfr$x), axes = FALSE)
Axis(side = 2)
Axis(at = h$breaks, labels = 10^h$breaks, side = 1)
For completeness, the lattice solution would be
library(lattice)
histogram(~x, dfr, scales = list(x = list(log = TRUE)))
AN EXPLANATION OF WHY LOG VALUES ARE NEEDED IN THE BASE CASE:
If you plot the data with no log-transformation, then most of the data are clumped into bars at the left.
hist(dfr$x)
The hist function ignores the log argument (because it interferes with the calculation of breaks), so this doesn't work.
hist(dfr$x, log = "y")
Neither does this.
par(xlog = TRUE)
hist(dfr$x)
That means that we need to log transform the data before we draw the plot.
hist(log10(dfr$x))
Unfortunately, this messes up the axes, which brings us to workaround above.
Using ggplot2 seems like the most easy option. If you want more control over your axes and your breaks, you can do something like the following :
EDIT : new code provided
x <- c(rexp(1000,0.5)+0.5,rexp(100,0.5)*100)
breaks<- c(0,0.1,0.2,0.5,1,2,5,10,20,50,100,200,500,1000,10000)
major <- c(0.1,1,10,100,1000,10000)
H <- hist(log10(x),plot=F)
plot(H$mids,H$counts,type="n",
xaxt="n",
xlab="X",ylab="Counts",
main="Histogram of X",
bg="lightgrey"
)
abline(v=log10(breaks),col="lightgrey",lty=2)
abline(v=log10(major),col="lightgrey")
abline(h=pretty(H$counts),col="lightgrey")
plot(H,add=T,freq=T,col="blue")
#Position of ticks
at <- log10(breaks)
#Creation X axis
axis(1,at=at,labels=10^at)
This is as close as I can get to the ggplot2. Putting the background grey is not that straightforward, but doable if you define a rectangle with the size of your plot screen and put the background as grey.
Check all the functions I used, and also ?par. It will allow you to build your own graphs. Hope this helps.
A dynamic graph would also help in this plot. Use the manipulate package from Rstudio to do a dynamic ranged histogram:
library(manipulate)
data_dist <- table(data)
manipulate(barplot(data_dist[x:y]), x = slider(1,length(data_dist)), y = slider(10, length(data_dist)))
Then you will be able to use sliders to see the particular distribution in a dynamically selected range like this:
Occasionally hist(..., nclass=nclass.scott) produces a histogram where the maximum bar extends over the top of the y axis. You may try this example a few times:
x <- sample(1000000, 500, replace=TRUE)
h <- hist(x,nclass=nclass.scott)
text(x=h$mids, y=h$counts, labels=h$counts, pos=3, col="red")
Example:
Occasionally the red number over the highest bar cannot be presented as it seems to be clipped by the plot region. I could add ylim=..., but it's quite tricky to get the maximum height of the bar.
Even when knowing the maximum height, ylim=(0, max) has the problem that max may be ignored: For example, when maximum is 527, then the upper displayed y-axis label is 500, even if ylim=(0, 527) is specified. When using 600 instead, it works, but then the y-axis is a bit too long...
If that is not a bug of R (3.3.3), what is an elegant (minimalistic) solution?
I think you need to set par(xpd= T) in your graph to avoid the trimming.
?par
xpd
A logical value or NA. If FALSE, all plotting is clipped to the
plot region, if TRUE, all plotting is clipped to the figure region,
and if NA, all plotting is clipped to the device region. See also
clip.
You can do it better by collaborating with usr option and xpd.Upon observation the bars seems going out of chart but it is not the bars that are going outside the chart but the axis being restricted to the labels. Hence to fix the labels we can choose to use usr. In case someone wants to play with the margin, one can also use mar.
library(RColorBrewer)
par(mfrow=c(1,1),xpd=T,yaxs="i")
x <- sample(1000000, 500, replace=TRUE)
h <- hist(x,nclass=nclass.scott,axes=FALSE,col=brewer.pal(10,"Set3"))
# usr <- par("usr")
at <- c(0, 10,30, par("usr")[4])
axis(2,at=at,labels = round(at))
text(x=h$mids, y=h$counts, labels=h$counts, pos=3, col="red")
usr
A vector of the form c(x1, x2, y1, y2) giving the extremes of the
user coordinates of the plotting region. When a logarithmic scale is
in use (i.e., par("xlog") is true, see below), then the x-limits will
be 10 ^ par("usr")[1:2]. Similarly for the y-axis.
You may want to run it several times, I have run it for many times, the bar won't seems to go outside the chart now.
Output:
What you describe is not a bug. You are using functionality to draw a histogram and then you want to add text to it. The function has not been designed for that, hence you need to reserve some additional white space for the text.
I suggest you run the function once, to get the "base values" of the graph. Then run the function again with adjusted scale (extra space for the text). In order to achieve this, you could use the following code
set.seed(9876) ### for reproducibility
x <- sample(1000000, 500, replace = TRUE)
h <- hist(x, nclass = nclass.scott, plot = FALSE)
### use the info from the previous call to adjust the y-scale with a constant
hist(x, nclass = nclass.scott, ylim = c(0, max(h$counts) + 10))
text(x = h$mids, y = h$counts, labels = h$counts, pos = 3, col = "red")
### ... or add a proportion (a little bit more robust)
hist(x, nclass = nclass.scott, ylim = c(0, max(h$counts) * 1.075))
text(x = h$mids, y = h$counts, labels = h$counts, pos = 3, col = "red")
Please let me know whether this is what you want.
When I manually add the following labels with (axis(1, at=1:27, labels=labs[0:27])):
> labs[0:27]
[1] "0\n9.3%" "1\n7.6%" "2\n5.6%" "3\n5.1%" "4\n5.7%" "5\n6.5%" "6\n7.3%" "7\n7.6%" "8\n7.5%" "9\n7%" "10\n6.2%" "11\n5.2%"
[13] "12\n4.2%" ........
I get the following:
How do I force all labels to be drawn so 1,3,5,6, and 11 are not skipped? (also, for extra credit, how do I shift the whole thing down a few pixels?)
If you want to force all labels to display, even when they are very close or overlapping, you can "trick" R into displaying them by adding odd and even axis labels with separate calls to the axis function, as follows:
labs <-c("0\n9.3%","1\n7.6%","2\n5.6%","3\n5.1%","4\n5.7%","5\n6.5%","6\n7.3%",
"7\n7.6%","8\n7.5%","9\n7%", "10\n6.2%","11\n5.2%","12\n4.2%",13:27)
n=length(labs)
plot(1:28, xaxt = "n")
axis(side=1, at=seq(1,n,2), labels=labs[seq(1,n,2)], cex.axis=0.6)
axis(side=1, at=seq(2,n,2), labels=labs[seq(2,n,2)], cex.axis=0.6)
You can play with cex.axis to get the text size that you want. Note, also, that you may have to adjust the number of values in at= and/or labels= so that they are equal.
I agree with #PLapointe and #joran that it's generally better not to tamper with R's default behavior regarding overlap. However, I've had a few cases where axis labels looked fine even when they weren't quite a full "m-width" apart, and I hit on the trick of alternating odd and even labels as a way to get the behavior I wanted.
?axis tells you that:
The code tries hard not to draw overlapping tick labels, and so will omit labels where they would abut or overlap previously drawn labels. This can result in, for example, every other tick being labelled. (The ticks are drawn left to right or bottom to top, and space at least the size of an ‘m’ is left between labels.)
Play with cex.axis so that labels are small enough to fit without overlapping
labs <-c("0\n9.3%","1\n7.6%","2\n5.6%","3\n5.1%","4\n5.7%","5\n6.5%","6\n7.3%",
"7\n7.6%","8\n7.5%","9\n7%", "10\n6.2%","11\n5.2%","12\n4.2%",12:27)
plot(1:27,xaxt = "n")
axis(side=1, at=1:27, labels=labs[0:27],cex.axis=0.35)
If you widen you graph (manually by dragging or programmatically), you can increase the size of your labels.
Although there are some good answers here, the OP didn't want to resize the labels or change anything about the plot besides fitting all of the axis labels. It's annoying, since often there appears to be plenty of room to fit all of the axis labels.
Here's another solution. Draw the plot without the axis, then add ticks with empty labels. Store the positions of the ticks in an object, so then you can go through each one and place it in the correct position on the axis.
plot(1:10, 1:10, yaxt = "n")
axis_ticks = axis(2, axTicks(2), labels = rep("", length(axTicks(2))))
for(i in axis_ticks) axis(2, i)
#PLapointe just posted what I was going to say, but omitted the bonus answer.
Set padj = 0.5 in axis to move the labels down slightly.
Perhaps draw and label one tick at a time, by calling axis repeatedly using mapply...
For example, consider the following data:
x = runif(100)*20
y = 10^(runif(100)*3)
The formula for y might look a bit odd; it gives random numbers distributed across three orders of magnitude such that the data will be evenly distributed on a plot where the y axis is on a log scale. This will help demonstrate the utility of axTicks() by calculating nice tick locations for us on a logged axis.
By default:
plot(x, y, log = "y")
returns:
Notice that 100 and 1000 labels are missing.
We can instead use:
plot(x, y, log = "y", yaxt = "n")
mapply(axis, side = 2, at = axTicks(2), labels = axTicks(2))
which calls axis() once for each tick location returned by axTicks(), thus plotting one tick at a time. The result:
What I like about this solution is that is uses only one line of code for drawing the axis, it prints exactly the default axis R would have made, except all ticks are labeled, and the labels don't go anywhere when the plot is resized:
I can't say the axis is useful in the resized example, but it makes the point about axis labels being permanent!
For the first (default) plot, note that R will recalculate tick locations when resizing.
For the second (always labeled) plot, the number and location of tick marks are not recalculated when the image is resized. The axis ticks calculated by axTicks depend upon the size of the display window when the plot is first drawn.
If you want want to force specific tick locations, try something like:
plot(x, y, log = "y", yaxt = "n")
mapply(axis, side = 2, at = c(1,10,100, 1000), labels = c("one", "ten", "hundred", "thousand"))
which yields:
axis() includes a gap.axis parameter that controls when labels are omitted. Setting this to a very negative number will force all labels to display, even if they overlap.
The padj parameter of axis() controls the y offset whilst plotting an individual axis.
par(mgp = c(3, 2, 0) will adjust the position of all axis labels for the duration of a plotting session: the second value (here 2, default 1) controls the position of the labels.
# Set axis text position, including for Y axis
par(mgp = c(3, 2, 0))
# Plot
plot(1:12, 1:12, log = 'x', ann = FALSE, axes = FALSE)
# Some numbers not plotted:
axis(1, 1:12)
# All numbers plotted, with manual offset
axis(1, 1:12, gap.axis = -100, padj = 0.5)
I had a similar problem where I wanted to stagger the labels and get them to print without losing some. I created two sets of ticks showing second set below the other to make it look as if it staggers.
xaxis_stagger = function(positions,labels) {
odd=labels[seq(1,length(labels),2)]
odd_pos=positions[seq(1,length(positions),2)]
even=labels[seq(2,length(labels),2)]
even_pos=positions[seq(2,length(positions),2)]
axis(side=1,at=odd_pos,labels=odd)
axis(side=1,at=even_pos,labels=even,padj=1.5)
}
So you give the positions where you want the ticks to be and the labels for those ticks and this would then re-organise it into two sets of axis and plot them on the original plot. Original plot would be done with xaxt="n".
I have data that is mostly centered in a small range (1-10) but there is a significant number of points (say, 10%) which are in (10-1000). I would like to plot a histogram for this data that will focus on (1-10) but will also show the (10-1000) data. Something like a log-scale for th histogram.
Yes, i know this means not all bins are of equal size
A simple hist(x) gives
while hist(x,breaks=c(0,1,1.1,1.2,1.3,1.4,1.5,1.6,1.7,1.8,1.9,2,3,4,5,7.5,10,15,20,50,100,200,500,1000,10000))) gives
none of which is what I want.
update
following the answers here I now produce something that is almost exactly what I want (I went with a continuous plot instead of bar-histogram):
breaks <- c(0,1,1.1,1.2,1.3,1.4,1.5,1.6,1.7,1.8,1.9,2,4,8)
ggplot(t,aes(x)) + geom_histogram(colour="darkblue", size=1, fill="blue") + scale_x_log10('true size/predicted size', breaks = breaks, labels = breaks)![alt text][3]
the only problem is that I'd like to match between the scale and the actual bars plotted. There two options for doing that : the one is simply use the actual margins of the plotted bars (how?) then get "ugly" x-axis labels like 1.1754,1.2985 etc. The other, which I prefer, is to control the actual bins margins used so they will match the breaks.
Log scale histograms are easier with ggplot than with base graphics. Try something like
library(ggplot2)
dfr <- data.frame(x = rlnorm(100, sdlog = 3))
ggplot(dfr, aes(x)) + geom_histogram() + scale_x_log10()
If you are desperate for base graphics, you need to plot a log-scale histogram without axes, then manually add the axes afterwards.
h <- hist(log10(dfr$x), axes = FALSE)
Axis(side = 2)
Axis(at = h$breaks, labels = 10^h$breaks, side = 1)
For completeness, the lattice solution would be
library(lattice)
histogram(~x, dfr, scales = list(x = list(log = TRUE)))
AN EXPLANATION OF WHY LOG VALUES ARE NEEDED IN THE BASE CASE:
If you plot the data with no log-transformation, then most of the data are clumped into bars at the left.
hist(dfr$x)
The hist function ignores the log argument (because it interferes with the calculation of breaks), so this doesn't work.
hist(dfr$x, log = "y")
Neither does this.
par(xlog = TRUE)
hist(dfr$x)
That means that we need to log transform the data before we draw the plot.
hist(log10(dfr$x))
Unfortunately, this messes up the axes, which brings us to workaround above.
Using ggplot2 seems like the most easy option. If you want more control over your axes and your breaks, you can do something like the following :
EDIT : new code provided
x <- c(rexp(1000,0.5)+0.5,rexp(100,0.5)*100)
breaks<- c(0,0.1,0.2,0.5,1,2,5,10,20,50,100,200,500,1000,10000)
major <- c(0.1,1,10,100,1000,10000)
H <- hist(log10(x),plot=F)
plot(H$mids,H$counts,type="n",
xaxt="n",
xlab="X",ylab="Counts",
main="Histogram of X",
bg="lightgrey"
)
abline(v=log10(breaks),col="lightgrey",lty=2)
abline(v=log10(major),col="lightgrey")
abline(h=pretty(H$counts),col="lightgrey")
plot(H,add=T,freq=T,col="blue")
#Position of ticks
at <- log10(breaks)
#Creation X axis
axis(1,at=at,labels=10^at)
This is as close as I can get to the ggplot2. Putting the background grey is not that straightforward, but doable if you define a rectangle with the size of your plot screen and put the background as grey.
Check all the functions I used, and also ?par. It will allow you to build your own graphs. Hope this helps.
A dynamic graph would also help in this plot. Use the manipulate package from Rstudio to do a dynamic ranged histogram:
library(manipulate)
data_dist <- table(data)
manipulate(barplot(data_dist[x:y]), x = slider(1,length(data_dist)), y = slider(10, length(data_dist)))
Then you will be able to use sliders to see the particular distribution in a dynamically selected range like this: