ggplot(f0peruttnq, aes(f0)) +
  geom_histogram(alpha=0.3, fill='white', colour='black')

ggplot(data, aes(V2)) + geom_histogram(alpha=0.3, fill='white', colour='black')+scale_x_log10(breaks=c(50,100,150,200,250),labels=c(50,100,150,200,250))

library(ggplot2)
dat <- subset(movies, votes > 1000)
m <- qplot(rating, votes, data=dat, na.rm = T)
bks <- seq(min(dat$rating),max(dat$rating))
m + scale_x_log10(breaks=bks,labels=bks)

> data <- log(rnorm(10000, 100, 10))  #simulate some data that looks like yours
> hist(data) # view a normal histogram of the data with log values on the x-axis
> tick_locations = c(4.2, 4.4, 4.6, 4.8, 5.0)  # copy the tick locations from the normal plot
> tick_labels = exp(tick_locations) # reverse the log transformation; you can also create this manually
> hist(data, xaxt = "n")  # plot without the x-axis
> axis(1, at = tick_locations, labels = tick_labels) # add the x-axis with the de-transformed values