Plotting two different distribution functions in R. Getting axis withing positive range of values

Question

I was following this https://stackoverflow.com/a/3542115/3483997 approach in order to get 2 histograms (with different populations) integrated in the same data-frame.

ROS_SPITFIRE <- data.frame(length = rnorm(100, 0.76406353, 0.500970292)) ROS_FARSITE <- data.frame(length = rnorm(398, 3.48366834170854,2.19050069588744))

#Now, combine your two dataframes into one. First make a new column in each. ROS_SPITFIRE$veg <- 'ROS_SPITFIRE' ROS_FARSITE$veg <- 'ROS_FARSITE'

#and combine into your new data frame vegLengths vegLengths <- rbind(ROS_SPITFIRE, ROS_FARSITE)

#now make your lovely plot ggplot(vegLengths, aes(length, fill = veg)) + geom_density(alpha = 0.3) ggplot(vegLengths, aes(length, fill = veg)) + geom_density(alpha = 0.3)

ggplot(vegLengths, aes(length, fill = veg)) + geom_histogram(alpha = 0.5, aes(y = ..density..), position = 'identity') ggplot = ggplot + xlim((0,15))

My problem popped up when I´ve created the new column in each data-frame. It generates negative values, hence my final distribution plots have negative values on the X-axes. Does anyone know how to fix it?

Thx

Answer 1

If you need to stick with the specific means and sds used but exclude any negative values you can filter the datasets e.g. ROS_SPITFIRE[ROS_SPITFIRE$length>0,] or do limits on the chart e.g. xlim(0,12).

If you can amend the distribution you can pick distributions or values that do not result in negative values. @Dave and @jbaum provide guidance like using sample(seq(.1, 1, by = .1), 100, replace = T) or evaluating other distribution options for going down this route.

You can also cut out some steps by going straight to charting and provide a limit:

ggplot(ROS_SPITFIRE, aes(length, y = ..density..,fill="spitfire")) + 
geom_histogram(alpha = 0.5,  position = 'identity')+ 
geom_histogram(data=ROS_FARSITE, aes(fill="farsite"), 
                 alpha = 0.5, position = 'identity')+
xlim(0,12)