boxplot

问题 Here my script to generate boxplot from precomputed data : mydata <-structure(list(v_rank=1:100,min=c(1876.12908723494,525.833257030355, 479.174444926073,413.317971868729,283.212605297879,272.271743111746, 271.218577609491,261.097920232602,249.848244413854,239.6826693619, 221.953200543177,220.672797573803,217.788754899515,209.693597246165, 207.920376492108,206.305695354979,205.224940348855,198.158941191935, 196.768964078812,192.524762910127,190.659747088907,187.313079645817, 184.003802843274

问题 I have a data frame with several groups values, and I would like to have a boxplot per category (drawn together). I want to have each boxplot with a different width, based not on the rows count per category, but on a column sum. For example, with the following data.frame: Data <- data.frame(roadType = sample(c("Ramp", "Primary Street", "Highway"),100,replace=TRUE), drivesCount = sample(1:100,100,replace=TRUE), happyPercentage=sample(c(0,0.25,0.5,0.75,1),100,replace=TRUE)) I know there's a way

问题 I have a data frame with several groups values, and I would like to have a boxplot per category (drawn together). I want to have each boxplot with a different width, based not on the rows count per category, but on a column sum. For example, with the following data.frame: Data <- data.frame(roadType = sample(c("Ramp", "Primary Street", "Highway"),100,replace=TRUE), drivesCount = sample(1:100,100,replace=TRUE), happyPercentage=sample(c(0,0.25,0.5,0.75,1),100,replace=TRUE)) I know there's a way

问题 I am trying to create a boxplot that shows all of the factors of a variable, along with sample size, and at eh end of the plot also want an overall boxplot that combines all of the values into one. I am using the following line of code to do everything except making the overall plot: library(ggplot2) library(plyr) xlabels <- ddply(extract8, .(Fuel), summarize, xlabels = paste(unique(Fuel), '\n(n = ', length(Fuel),')')) ggplot(extract8, aes(x = Fuel, y = Exfiltration.Fraction.Percentage))+geom

问题 I have to plot a boxplot of some data, which I could easily do with Matplotlib . However, I was requested to provide a table with the data presented there, like the whiskers, the medians, standard deviation, and so on. I know that I could calculate these "by hand", but I also know, from the reference, that the boxplot method: Returns a dictionary mapping each component of the boxplot to a list of the matplotlib.lines.Line2D instances created. That dictionary has the following keys (assuming

问题 I have three dataframes containing 17 sets of data with groups A, B, and C. A shown in the following code snippet import pandas as pd import numpy as np data1 = pd.DataFrame(np.random.rand(17,3), columns=['A','B','C']) data2 = pd.DataFrame(np.random.rand(17,3)+0.2, columns=['A','B','C']) data3 = pd.DataFrame(np.random.rand(17,3)+0.4, columns=['A','B','C']) I would like to plot a box plot to compare the three groups as shown in the figure below I am trying make the plot using seaborn's box

问题 I have some data here [in a .txt file] which I read into a data frame df, df <- read.table("data.txt", header=T,sep="\t") I remove the negative values in the column x (since I need only positive values) of the df using the following code, yp <- subset(df, x>0) Now I want plot multiple box plots in the same layer. I first melt the data frame df , and the plot which results contains several outliers as shown below. # Melting data frame df df_mlt <-melt(df, id=names(df)[1]) # plotting the

问题 I have generated a random set of data here, as I cannot post my own. It's not great data but it should illustrate what I'm trying to do. Specifically, I have three treatments, the effects of which are being measured each year. Each treatment is replicated 6 times each year. I want to plot the effect of treatment on the Dependent variable (DV) with year (i.e. over the course of the study) using ggplot2 I have tried: ggplot(test, aes(x = factor(Year), y = DV, fill = factor(Grp))) + geom_boxplot

问题 I am a beginner, so please bear with me. I make a violin plot with "five violins" but because of some reason, the last violin is not drawn and I get the error message: /home/leo/anaconda3/lib/python3.6/site-packages/numpy/ma/core.py:4185: UserWarning: Warning: converting a masked element to nan. I don't understand why I get this message because I didn't use a mask for any array. So what does it actually mean? Also some more warnings like: Invalid value encountered in percentile I guess it is

问题 I have a dataset which looks like this VegType 87MIN 87MAX 87Q25 87Q50 87Q75 96MIN 96MAX 96Q25 96Q50 96Q75 00MIN 00MAX 00Q25 00Q50 00Q75 1 0.02 0.32 0.11 0.12 0.13 0.02 0.26 0.08 0.09 0.10 0.02 0.28 0.10 0.11 0.12 2 0.02 0.45 0.12 0.13 0.13 0.02 0.20 0.09 0.10 0.11 0.02 0.26 0.11 0.12 0.12 3 0.02 0.29 0.13 0.14 0.14 0.02 0.27 0.11 0.11 0.12 0.02 0.26 0.12 0.13 0.13 4 0.02 0.41 0.13 0.13 0.14 0.02 0.58 0.10 0.11 0.12 0.02 0.34 0.12 0.13 0.13 5 0.02 0.42 0.12 0.13 0.14 0.02 0.46 0.10 0.11 0.11