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    <p>I think the key thing is that you need to do the frequency calculation outside of ggplot. Use aggregate() with geom_bar(stat="identity") to get a histogram without the reordered factors. Here is some example code:</p> <pre><code>require(ggplot2) # scales goes with ggplot and adds the needed scale* functions require(scales) # need the month() function for the extra plot require(lubridate) # original data #df&lt;-read.csv("http://pastebin.com/download.php?i=sDzXKFxJ", header=TRUE) # simulated data years=sample(seq(2008,2012),681,replace=TRUE,prob=c(0.0176211453744493,0.302496328928047,0.323054331864905,0.237885462555066,0.118942731277533)) months=sample(seq(1,12),681,replace=TRUE) my.dates=as.Date(paste(years,months,01,sep="-")) df=data.frame(YM=strftime(my.dates, format="%Y-%b"),Date=my.dates,Year=years,Month=months) # end simulated data creation # sort the list just to make it pretty. It makes no difference in the final results df=df[do.call(order, df[c("Date")]), ] # add a dummy column for clarity in processing df$Count=1 # compute the frequencies ourselves freqs=aggregate(Count ~ Year + Month, data=df, FUN=length) # rebuild the Date column so that ggplot works freqs$Date=as.Date(paste(freqs$Year,freqs$Month,"01",sep="-")) # I set the breaks for 2 months to reduce clutter g&lt;-ggplot(data=freqs,aes(x=Date,y=Count))+ geom_bar(stat="identity") + scale_x_date(labels=date_format("%Y-%b"),breaks="2 months") + theme_bw() + opts(axis.text.x = theme_text(angle=90)) print(g) # don't overwrite the previous graph dev.new() # just for grins, here is a faceted view by year # Add the Month.name factor to have things work. month() keeps the factor levels in order freqs$Month.name=month(freqs$Date,label=TRUE, abbr=TRUE) g2&lt;-ggplot(data=freqs,aes(x=Month.name,y=Count))+ geom_bar(stat="identity") + facet_grid(Year~.) + theme_bw() print(g2) </code></pre>
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    1. POUnderstanding dates and plotting a histogram with ggplot2 in R
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    1. COJust saw this. I plan to work through it... but it seems this would have been a lot easier to just use the data I already provided. Is there a reason you didn't do that? It has both a `%Y-%b` and `%Y-%m-%d` set of values that should have made it possible to work with?
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    2. COSee update section in my question. I was able to apply your use of aggregate to do pretty much exactly what I want to do. Take a look; I think you don't need your `df$Count` vector or some other other things you did to get a usable result. Now I'd just like to know how to set limits based on date ranges. I also didn't need `lubridate`.
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    3. COI included dummy data for posterity. The StackOverflow question may remain while the pastebin entry disappears. In that case, my answer will still work as written. You are correct, lubridate is only needed for the second graph, not the first.
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