boxplot

I can't find a way to ask ggplot2 to show an empty level in a boxplot without imputing my dataframe with actual missing values. Here is reproducible code : # fake data dftest <- expand.grid(time=1:10,measure=1:50) dftest$value <- rnorm(dim(dftest)[1],3+0.1*dftest$time,1) # and let's suppose we didn't observe anything at time 2 # doesn't work even when forcing with factor(..., levels=...) p <- ggplot(data=dftest[dftest$time!=2,],aes(x=factor(time,levels=1:10),y=value)) p + geom_boxplot() # only way seems to have at least one actual missing value in the dataframe dftest2 <- dftest dftest2

I'm trying to plot a boxplot graph with my data, using 'ggplot' in R, but I just can't do it. Can anyone help me out? The data is like the table below: Paratio ShapeIdx FracD NNDis Core -3.00 1.22 0.14 2.71 7.49 -1.80 0.96 0.16 0.00 7.04 -3.00 1.10 0.13 2.71 6.85 -1.80 0.83 0.16 0.00 6.74 -0.18 0.41 0.27 0.00 6.24 -1.66 0.12 0.11 2.37 6.19 -1.07 0.06 0.14 0.00 6.11 -0.32 0.18 0.23 0.00 5.93 -1.16 0.32 0.15 0.00 5.59 -0.94 0.14 0.15 1.96 5.44 -1.13 0.31 0.16 0.00 5.42 -1.35 0.40 0.15 0.00 5.38 -0.53 0.25 0.20 2.08 5.32 -1.96 0.36 0.12 0.00 5.27 -1.09 0.07 0.13 0.00 5.22 -1.35 0.27 0.14 0.00 5

I have constructed some box-plots in R and have several outliers. I know that the default criteria to set outlier limits are: Q3 + 1.5*IQR Q1 - 1.5* IQR However, I would like outliers classified as values that fall outside of the boundaries: Q3 + 3*IQR Q1 - 3* IQR Is it possible to set this in R? From ?boxplot range : this determines how far the plot whiskers extend out from the box. If ‘range’ is positive, the whiskers extend to the most extreme data point which is no more than ‘range’ times the interquartile range from the box. A value of zero causes the whiskers to extend to the data

I am trying to find a suitable display to illustrate various properties within and across school classes. For each class there is only 15-30 data points (pupils). Right now i am leaning towards a whisker-less boxplot, showing only 1.,2. and 3. quartile + datapoints more then e.g. 1 population SD +/- the sample median. This I can do. However - I need to show this graph to some teachers, in order to gauge what they like most. I'd like to compare my graph with a normal boxplot. But the normal boxplot looks the same if there is only one outlier, or e.g. 5 outliers at the same value. In this case

I have seen this wonderful boxplot in this article (Fig.2). As you can see, this is a boxplot on which are superimposed a scatter of black points: x indexes the black points (in a random order), y is the variable of interest. I would like to do something similar using Matplotlib, but I have no idea where to start. So far, the boxplots which I have found online are way less cool and look like this: Documentation of matplotlib: http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.boxplot Ways to colorize boxplots: https://github.com/jbmouret/matplotlib_for_papers#colored-boxes Kyrubas

I would like to create boxplots of multiple variables for groups of a continuous x-variable. The boxplots should be arranged next to each other for each group of x. The data looks like this: require (ggplot2) require (plyr) library(reshape2) set.seed(1234) x <- rnorm(100) y.1 <- rnorm(100) y.2 <- rnorm(100) y.3 <- rnorm(100) y.4 <- rnorm(100) df <- as.data.frame(cbind(x,y.1,y.2,y.3,y.4)) which I then melted dfmelt <- melt(df, measure.vars=2:5) The facet_wrap as shown in this solution ( Multiple plots by factor in ggplot (facets) ) gives me out each variable in an individual plot, but I would