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.

Another option would be to use the package ggplot2.

ggplot(mydata, aes(x = V3)) + geom_histogram() + scale_x_log10()

It's not entirely clear from your question whether you want a logged x-axis or a logged y-axis. A logged y-axis is not a good idea when using bars because they are anchored at zero, which becomes negative infinity when logged. You can work around this problem by using a frequency polygon or density plot.

Dirk's answer is a great one. If you want an appearance like what hist produces, you can also try this:

buckets <- c(0,1,2,3,4,5,25)
mydata_hist <- hist(mydata$V3, breaks=buckets, plot=FALSE)
bp <- barplot(mydata_hist$count, log="y", col="white", names.arg=buckets)
text(bp, mydata_hist$counts, labels=mydata_hist$counts, pos=1)

The last line is optional, it adds value labels just under the top of each bar. This can be useful for log scale graphs, but can also be omitted.

I also pass main, xlab, and ylab parameters to provide a plot title, x-axis label, and y-axis label.