How can I plot a histogram of a long-tailed data using R?

后端 未结 3 1813
渐次进展
渐次进展 2020-12-13 16:18

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 f

相关标签:
3条回答
  • 2020-12-13 16:34

    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: enter image description here

    0 讨论(0)
  • 2020-12-13 16:43

    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.

    0 讨论(0)
  • 2020-12-13 16:49

    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.

    alt text

    0 讨论(0)
提交回复
热议问题