boxplot

问题 Being new to R, I have some problems in mind. Can you guys help me with it? I have a series of data X Gender Score Postal 1 F 427.395 123455 2 F 922.080 642362 3 M 114.500 123947 4 M 176.345 236835 5 F 523.140 849729 Above is a sample of 500 data. I wish to do a boxplot on scores for females and males separately and also. However, there's the postal code which will be captured in the boxplot as well. How do I make the conditions for boxplot to capture data from only X and Score, classified by

问题 I have the following data frame: value total_spend margin 1 29493.14 10203.37 1 27551.22 19003.07 2 22881.26 15142.68 1 15254.77 12337.22 1 11873.95 9424.23 1 11382.89 8767.83 1 11006.11 6867.29 2 9647.16 7543.24 2 9227.57 9227.57 1 9077.39 6541.60 1 8912.10 4074.26 2 8560.05 7466.30 1 8041.52 7425.49 1 8007.19 5850.35 1 7914.47 3363.42 2 7812.48 4185.71 2 7441.81 7341.23 1 7388.98 6871.19 i need to make a two box plot from'total_spend' column for every group of 'value' . two box plot in the

问题 I have created boxplots using ggplot2 with this code. plotgraph <- function(x, y, colour, min, max) { plot1 <- ggplot(dims, aes(x = x, y = y, fill = Region)) + geom_boxplot() #plot1 <- plot1 + scale_x_discrete(name = "Blog Type") plot1 <- plot1 + labs(color='Region') + geom_hline(yintercept = 0, alpha = 0.4) plot1 <- plot1 + scale_y_continuous(breaks=c(seq(min,max,5)), limits = c(min, max)) plot1 <- plot1 + labs(x="Blog Type", y="Dimension Score") + scale_fill_grey(start = 0.3, end = 0.7) +

问题 I would like to flip the coords for a ggplot2 boxplot where I also do a coordinate transformation. library(ggplot2) dat = data.frame(group = factor(c(rep(1,3),rep(2,6))), vals = c(c(0.1,2.25,1000), c(0.11,0.21,0.21,4.55,5.06,29.48))) ggplot(dat,aes(group,vals)) + geom_boxplot() ggplot(dat,aes(group,vals)) + geom_boxplot() + coord_trans(y="log10") If I just add now "+ coord_flip()", the log scaling of the axis is lost.. ggplot(dat,aes(group,vals)) + geom_boxplot() + coord_trans(y="log10") +

问题 I'm trying to add a label on boxplot using ggpubr package. Here's the code I used: library(ggplot2) library(ggpubr) compare_means(len ~ supp, data = ToothGrowth, method="t.test", paired=TRUE, group.by = "dose") # Box plot facetted by "dose" p1 <- ggboxplot(ToothGrowth, x = "supp", y = "len", xlab=F, color = "supp", palette = "jco", facet.by = "dose", add="mean", short.panel.labs = FALSE) # Use only p as label. p2 <- p1 + stat_compare_means(method = "t.test", paired = T, label = "p") p2 And

问题 I am trying to display grouped boxplot and combined boxplot into one plot. Take the iris data for instance: data(iris) p1 <- ggplot(iris, aes(x=Species, y=Sepal.Length)) + geom_boxplot() p1 I am trying to compare overall distribution with distributions within each categories. So is there a way to display a boxplot of all samples on the left of these three grouped boxplots? Thanks in advance. 回答1: You can rbind a new version of iris , where Species equals "All" for all rows, to iris before

问题 I have a continuous variable y measured on different dates. I need to make boxplots with a box showing the distribution of y for each 5 year interval. Sample data: rdob <- as.Date(dob, format= "%m/%d/%y") ggplot(data = data, aes(x=rdob, y=ageyear)) + geom_boxplot() #Warning message: #Continuous x aesthetic -- did you forget aes(group=...)? This image is the first one I tried. What I want is a box for every five year interval, instead of a box for every year. 回答1: Here is a way to pull out the

问题 I would like to draw a bar chart with "unequal samples". Here is an example code A = [16 20 15 17 22 19 17]'; B = [22 15 16 16 16 18]'; C = [23 9 15 18 13 27 17 14 16 15 21 19 17]'; group = [ ones(size(A)); 2 * ones(size(B)); 3 * ones(size(C))]; figure boxplot([A; B; C],group) set(gca,'XTickLabel',{'A','B','C'}) The output is as below: However, I would like to have a distance between group1,2 with group 3. As same as what you see in the figure below:(this figure is just a copy paste from

问题 So I have a data frame, set up a bit like this: Sample V1 V2 V3 Group1 Group2 bob 12 32 12 G1 G2 susan 43 23 54 G2 G2 mary 23 65 34 G1 G2 I am able to do a grouped boxplot of each variable (V1, V2, V3) individually, grouped by Group1 and Group2 variables, but my real dataset has WAY more variables, and will be tedious to code individually. Is there a way that I can loop the process, and automate plot generation and export? For loops are still a bit of an obscure topic for me. Here is the code

问题 I'm trying to create a 4x4 FacetGrid in seaborn for 4 boxplots, each of which is split into 3 boxplots based on the iris species in the iris dataset. Currently, my code looks like this: sns.set(style="whitegrid") iris_vis = sns.load_dataset("iris") fig, axes = plt.subplots(2, 2) ax = sns.boxplot(x="Species", y="SepalLengthCm", data=iris, orient='v', ax=axes[0]) ax = sns.boxplot(x="Species", y="SepalWidthCm", data=iris, orient='v', ax=axes[1]) ax = sns.boxplot(x="Species", y="PetalLengthCm",