Histogram with "Negative" Logarithmic Scale in R

Histogram with Logarithmic Scale and custom breaks

A histogram is a poor-man's density estimate. Note that in your call to hist() using default arguments, you get frequencies not probabilities -- add ,prob=TRUE to the call if you want probabilities.

As for the log axis problem, don't use 'x' if you do not want the x-axis transformed:

plot(mydata_hist$count, log="y", type='h', lwd=10, lend=2)

gets you bars on a log-y scale -- the look-and-feel is still a little different but can probably be tweaked.

Lastly, you can also do hist(log(x), ...) to get a histogram of the log of your data.

Make y-axis logarithmic in histogram using R

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)')

Plot negative on logarithmic axis in ggplot

You can pmax(0, .) it:

library(ggplot2)
library(scales)

ggplot(df, aes(x = Sample, y = Fe, ymin = pmax(0, Fe - sd), ymax = Fe + sd)) +
  theme_bw() +
  geom_point(size=3, stat = "identity") + 
  geom_errorbar(aes(width = 0.1), stat = "identity") +
  scale_y_continuous(trans = log10_trans(),
                     breaks = trans_breaks("log10", function(x) 10^x),
                     labels = trans_format("log10", math_format(10^.x))) +
  annotation_logticks(sides = "l")

Or you can use a smaller number and see the lower end of that error bar, though that might suggest a present value that isn't ...

ggplot(df, aes(x = Sample, y = Fe, ymin = pmax(1, Fe - sd), ymax = Fe + sd)) +
  theme_bw() +
  geom_point(size=3, stat = "identity") + 
  geom_errorbar(aes(width = 0.1), stat = "identity") +
  scale_y_continuous(trans = log10_trans(),
                     breaks = trans_breaks("log10", function(x) 10^x),
                     labels = trans_format("log10", math_format(10^.x))) +
  annotation_logticks(sides = "l")

Using much smaller values will continue to squish the other errors a little tighter as the y-axis tries to adjust.

how to use a log scale for y-axis of histogram in R?

I would try using hist(log10(dall$seconds.alive)) instead.

Also try specifying breaks=100 or smaller/larger number:

hist(log10(dall$seconds.alive), breaks=100)

histogram in r on log-log scale displays only a limited amount of values

When you use in function plot() only object hist.a$count on the x axis you get just number corresponding to length of your object - they are not actual numbers of a values. You can add actual values later with axis() and taking labels= from hist.a$mids.

set.seed(5555)
a <- rlnorm(1000)
hist.a <- hist(a, plot = FALSE)

hist.a
  $breaks
  [1]  0  5 10 15 20 25 30 35 40

  $counts
  [1] 955  34   6   2   2   0   0   1

  $density
  [1] 0.1910 0.0068 0.0012 0.0004 0.0004 0.0000 0.0000 0.0002

  $mids
  [1]  2.5  7.5 12.5 17.5 22.5 27.5 32.5 37.5

  $xname
  [1] "a"

  $equidist
  [1] TRUE

  attr(,"class")
  [1] "histogram"

plot(hist.a$count, log = "xy",xaxt="n",type="h",lwd=10,lend=2)
axis(1,at=1:length(hist.a$mids),labels=hist.a$mids)

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