boxplot

I want to merge the three datasets grouped and obtain a graph with only two boxes, 1 for A and 1 for B. Can you suggest how to get that? I'm tryng to create a grouped boxplot in R. I have 2 groups: A and B, in each group I have 3 subgroups with 5 measurements each. The following is the way that I constructed the boxplot, but if someone has a better, shorter or easy way to do, I'll appreciate A1 <- c(1,2,9,6,4) A2 <- c(5,1,9,2,3) A3 <- c(1,2,3,4,5) B1 <- c(2,4,6,8,10) B2 <- c(0,3,6,9,12) B3 <- c(1,1,2,8,7) DF <- data.frame(A1, A2, A3, B1, B2, B3) boxplot(DF, col = rainbow(3, s = 0.5)) axis(side

How can I give the labels "a", "b", "c" individual colors (e.g. "a" in green, "b" in blue, "c" in red) in the example below? import numpy as np import matplotlib.pyplot as plt fig, ax = plt.subplots() p = plt.boxplot(np.random.normal(size=(10,3))) ax.set_xticklabels(list("abc")) plt.show() The code: import numpy as np import matplotlib.pyplot as plt fig, ax = plt.subplots() p = plt.boxplot(np.random.normal(size=(10,3))) ax.set_xticklabels(list("abc")) [t.set_color(i) for (i,t) in zip(['red','green','blue'],ax.xaxis.get_ticklabels())] plt.show() Gives me: 来源： https://stackoverflow.com/questions

From what I can see, boxplot() method expects a sequence of raw values (numbers) as input, from which it then computes percentiles to draw the boxplot(s). I would like to have a method by which I could pass in the percentiles and get the corresponding boxplot . For example: Assume that I have run several benchmarks and for each benchmark I've measured latencies ( floating point values ). Now additionally, I have precomputed the percentiles for these values. Hence for each benchmark, I have the 25th, 50th, 75th percentile along with the min and max. Now given these data, I would like to draw

If I have some data and do an ANOVA and post-hoc tests, how do I make a boxplot that adds the post-hoc classification automatically, rather than having to edit the figure outside of R? For example, here are some data to get started: install.packages("reshape", dependencies=T) library(reshape) x <- rnorm(30) y <- rnorm(30)+1 z <- rnorm(30)+0.5 data.1 <- data.frame(x, y, z) data.2 <- melt(data.1) Here's code for running a simple one way ANOVA and all of the unplanned comparision post-hoc tests: linear.model <- lm(value~variable, data=data.2) anova(linear.model) # Analysis of Variance Table #

I'm working on trying to make a boxplot in R-cran that is categorized by two different factors on the x-axis. My problem lies in creating labels for one factor with +20 levels that spans the entire graph appropriately while using a legend to label the second factor which has only 2 to 3 levels. Here is a test script that roughly mimics my actual dataset: d<-data.frame(x=rnorm(1500),f1=rep(seq(1:20),75),f2=rep(letters[1:3],500)) # first factor has 20+ levels d$f1<-factor(d$f1) # second factor a,b,c d$f2<-factor(d$f2) boxplot(x~f2*f1,data=d,col=c("red","blue","green"),frame.plot=TRUE,axes=FALSE)

I found some solutions but not exactly what I want. I have 5 dataframes in R and each dataframe has 4 columns: Lets say name of the first dataframe is "Gene1" Ind1 Ind2 Ind3 Ind4 1 3 3.2 2.5 1 3 4 2 1.5 2 2.2 1 3.4 2 1 3 and remaining dataframes are called "Gene2", "Gene3","Gene4","Gene5" and are similar. I want to plot boxplots side by side in same plot for all dataframes and for all columns. I did not find any plot like this, so I can't upload a picture but I will try to explain. Now from above data, the plot will have 20 box plots. First 4 box plot should be close to each other and x-axis

I need to do a boxplot (in Python and matplotlib) but I do not have the original "raw" data. What I have are precalculated values for max, min, mean, median and IQR (normal distribution) but still I'd like to do a boxplot. Of course plotting outliers isn't possible, but beside that I guess all information is there. I've search all over to find an answer without success. The closest I've come is the same question but for R (which I'm unfamiliar with). See Is it possible to plot a boxplot from previously-calculated statistics easily (in R?) Can anyone show me how to do the boxplot? Many thanks!

I have a dataset (test) as given below: Type Met1 Met2 Met3 Met4 TypeA 65 43 97 77 TypeA 46 25 76 77 TypeA 44 23 55 46 TypeA 46 44 55 77 TypeA 33 22 55 54 TypeB 66 8 66 47 TypeB 55 76 66 65 TypeB 55 77 88 46 TypeB 36 67 55 44 TypeB 67 55 76 65 I have checked a lot of links on box plots, but I still have not succeeded for the type of box plot I want. I wish to have a boxplot with my X-axis having type A (yellow, orange) for all the Mets (Met1, Met2, Met3, Met4). In essence, I want something like the following (taken from here ): I am trying somethings like, boxplot(formula = len ~ Type , data =