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PORemove a few text marks from tick marks in ggplot bar plot
 

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    <p>I am doing some research on non-defaulters and defaulters with regards to banking. In that context I am plotting their distributions relative to some score in a bar plot. The higher the score, the better the credit rating. </p> <p>Since the number of defaults is very limited compared to the number of non-defaults plotting the defaults and non-defaults on the same bar plot is not very giving as you hardly can see the defaults. I then make a second bar plot based on the defaulters' scores only, but on the same interval scale as the full bar plot of both the scores of the defaulters and non-defaulters. I then add vertical lines to the first bar plot indicating where the highest and the lowest defaulter score is located. That is to get a view of where the distribution of the defaulters fit into that of the overall distribution of both defaulters and non-defaulters. </p> <p>The x-axis easily gets very "crowded". I would like to remove some of the text for the ticks, but not all the tick marks.</p> <p>Below is the code I am using replaced with (seeded) random data instead.</p> <p>The first bar plot is what I would like to have with regards to text on the tick marks, but I am missing all the ticks I have in the second bar plot. In the second bar plot the "crowded"-ness is shown!</p> <pre><code>library(ggplot2) library(ggExtra) #NDS represents non-defaults and DS defaults on the same scale #although here being just some random normals for the sake of simplicity. set.seed(10) NDS&lt;-rnorm(10000,sd=1)-2 DS&lt;-rnorm(100,sd=2)-5 #Cutoffs are constructed such that intervals of size 0.3 contain all values #of NDS &amp; DS minCutoff&lt;--9.3 maxCutoff&lt;-2.1 #Generate the actual interval "bins" NDS_CUT&lt;-cut(NDS,breaks=seq(minCutoff, maxCutoff, by = 0.3)) DS_CUT&lt;-cut(DS,breaks=seq(minCutoff, maxCutoff, by = 0.3)) #Manually generate where to put the vertical lines for min(DS) and max(DS) minDS_bar&lt;-levels(cut(NDS,breaks=seq(minCutoff, maxCutoff, by = 0.3)))[1] maxDS_bar&lt;-levels(cut(NDS,breaks=seq(minCutoff, maxCutoff, by = 0.3)))[32] #Generate data frame - seems stupid, but makes sense #when the "real" data is used :-) NDSdataframe&lt;-cbind(as.data.frame(NDS_CUT),rep(factor("State-1"),length(NDS_CUT))) colnames(NDSdataframe)&lt;-c("Score","Action") DSdataframe&lt;-cbind(as.data.frame(DS_CUT),rep(factor("State-2"),length(DS_CUT))) colnames(DSdataframe)&lt;-c("Score","Action") fulldataframe&lt;-rbind(NDSdataframe,DSdataframe) attach(fulldataframe) #Plot the full distribution of NDS &amp; DS with geom_vlines #Get the tick texts I want to show myLevels&lt;-levels(cut(NDS,breaks=seq(roundDownNDS, roundUpNDS, by = 0.3))) lengthMyLevels&lt;-length(myLevels) myBreaks&lt;-seq(1,lengthMyLevels,3) chosenbreaks&lt;-myLevels[myBreaks[1]] for(i in 2:length(myBreaks)) { chosenbreaks&lt;-rbind(chosenbreaks,myLevels[myBreaks[i]]) } #Generate the plot of both NDS &amp; DS fullplot&lt;-ggplot(fulldataframe, aes(Score, fill=factor(Action,levels=c("State- 2","State-1")))) + geom_bar(position="stack") + opts(axis.text.x = theme_text(angle = 45,size=8)) + opts(legend.position = "none") + xlab("Scoreinterval") + ylab("Antal pr. interval") + geom_vline(aes(xintercept = minDS_bar, colour="red")) + geom_vline(aes(xintercept = maxDS_bar, colour="red")) + scale_x_discrete("test",breaks=chosenbreaks) #Generate second dataframe for the plot of DS only DSdataframe2&lt;-cbind(na.omit(as.data.frame(DS_CUT)),rep(factor("Fallit"),length (na.omit(as.data.frame(DS_CUT))))) colnames(DSdataframe2)&lt;-c("theScore","theAction") #Calculate max value for the DS myMax&lt;-max(table(DSdataframe2))+1 attach(DSdataframe2) #Generate plot for the DS only subplot&lt;-ggplot(fulldataframe, aes(theScore, fill=factor(theAction))) + geom_bar (position="stack") + opts(axis.text.x = theme_text(angle = 45)) + opts(legend.position = "none") + ylim(0, myMax) + xlab("Scoreinterval") + ylab("Antal pr. interval") #Using the ggExtra package the to plots are aligned align.plots(fullplot, subplot) detach(DSdataframe2) detach(fulldataframe) </code></pre> <p>Any help is very much appreciated!</p> <p>Thanks,</p> <p>Christian</p>
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