Hi I'm making histogram using R, but the number of Y axis is so large that I need to turn it into logarithmic.See below my script:
hplot<-read.table("libl")
hplot
pdf("first_end")
hist(hplot$V1, breaks=24, xlim=c(0,250000000), ylim=c(0,2000000),main="first end mapping", xlab="Coordinates")
dev.off()
So how should I change my script? thx
To change the axis scales on a plot in base R Language, we can use the xlim() and ylim() functions. The xlim() and ylim() functions are convenience functions that set the limit of the x-axis and y-axis respectively.
You can change the title of the histogram by adding main as an argument to hist() function. In this case, you make a histogram of the AirPassengers data set with the title “Histogram for Air Passengers”: If you want to adjust the label of the x-axis, add xlab .
You can save the histogram data to tweak it before plotting:
set.seed(12345)
x = rnorm(1000)
hist.data = hist(x, plot=F)
hist.data$counts = log10(hist.data$counts)
dev.new(width=4, height=4)
hist(x)
dev.new(width=4, height=4)
plot(hist.data, ylab='log10(Frequency)')
Another option would be to use plot(density(hplot$V1), log="y")
.
It's not a histogram, but it shows just about the same information, and it avoids the illogical part where a bin with zero counts is not well-defined in log-space.
Of course, this is only relevant when your data is continuous and not when it's really categorical or ordinal.
A histogram with the y-axis on the log scale will be a rather odd histogram. Technically it will still fit the definition, but it could look rather misleading: the peaks will be flattened relative to the rest of the distribution.
Instead of using a log transformation, have you considered:
Dividing the counts by 1 million:
h <- hist(hplot$V1, plot=FALSE)
h$counts <- h$counts/1e6
plot(h)
Plotting the histogram as a density estimate:
hist(hplot$V1, freq=FALSE)
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With