boxplot

问题 I want to plot both a boxplot and the mean in one figure. So far my plot looks like this using these lines of code: sns.swarmplot(x="stimulus", y="data", data=spi_num.astype(np.float), edgecolor="black", linewidth=.9) sns.boxplot(x="stimulus", y="data", data=spi_num.astype(np.float), saturation=1) sns.pointplot(x="stimulus", y="data", data=spi_num.astype(np.float), linestyles='', scale=1, color='k', errwidth=1.5, capsize=0.2, markers='x') sns.pointplot(x="stimulus", y="data", data=spi_num

问题 I want to plot both a boxplot and the mean in one figure. So far my plot looks like this using these lines of code: sns.swarmplot(x="stimulus", y="data", data=spi_num.astype(np.float), edgecolor="black", linewidth=.9) sns.boxplot(x="stimulus", y="data", data=spi_num.astype(np.float), saturation=1) sns.pointplot(x="stimulus", y="data", data=spi_num.astype(np.float), linestyles='', scale=1, color='k', errwidth=1.5, capsize=0.2, markers='x') sns.pointplot(x="stimulus", y="data", data=spi_num

问题 I want to plot both a boxplot and the mean in one figure. So far my plot looks like this using these lines of code: sns.swarmplot(x="stimulus", y="data", data=spi_num.astype(np.float), edgecolor="black", linewidth=.9) sns.boxplot(x="stimulus", y="data", data=spi_num.astype(np.float), saturation=1) sns.pointplot(x="stimulus", y="data", data=spi_num.astype(np.float), linestyles='', scale=1, color='k', errwidth=1.5, capsize=0.2, markers='x') sns.pointplot(x="stimulus", y="data", data=spi_num

问题 I am new with highcharts and javascript. I am trying to make a boxplot with drilldown. Chart type 'boxplot' requires data to be a array of 5 element(min 1st-quatile median 3st-quatile max), as follows: data: [ [760, 801, 848, 895, 965], [733, 853, 939, 980, 1080], [834, 836, 864, 882, 910] ] While drilldown requires that data should have many members, including "drilldown" member, as follow: data: [{ name: 'namey', y: 49.9, drilldown: 'tokyo 1' }, { y: 71.5, name: 'namex', drilldown: 'tokyo 2

问题 I am new with highcharts and javascript. I am trying to make a boxplot with drilldown. Chart type 'boxplot' requires data to be a array of 5 element(min 1st-quatile median 3st-quatile max), as follows: data: [ [760, 801, 848, 895, 965], [733, 853, 939, 980, 1080], [834, 836, 864, 882, 910] ] While drilldown requires that data should have many members, including "drilldown" member, as follow: data: [{ name: 'namey', y: 49.9, drilldown: 'tokyo 1' }, { y: 71.5, name: 'namex', drilldown: 'tokyo 2

问题 These two graphs have exactly the same x axis value of each point, is it possible to display the box whisker on top of the first graph? I tried this: fig1 = plt.figure() ax = fig1.add_subplot(211) ax.set_xscale('log') ax.plot(x7,y7,'c+-') ax.plot(x8,y8,'m+-') ax.plot(x9,y9,'g+-') ax.boxplot(dataset) xtickNames = plt.setp(ax, xticklabels=boxx) plt.setp(xtickNames) The results only display the box whisker graph without the other three lines, so, I tried this instead: fig1 = plt.figure() ax =

问题 I'm an undergrad researcher and I've been teaching myself R over the past few months. I just started trying ggplot, and have run into some trouble. I've made a series of boxplots looking at the depth of fish at different acoustic receiver stations. I'd like to add a scatterplot that shows the depths of the receiver stations. This is what I have so far: data <- read.csv(".....MPS.csv", header=TRUE) df <- data.frame(f1=factor(data$Tagging.location), #$ f2=factor(data$Station),data$Detection

问题 I have a matrix of 2 columns. I would like boxplot each of these columns but each has different number of entries. For example, first column has 10 entries and the second column has 7 entries. The remaining 3 of the second column is given zero. I would like to plot these side by side for comparison reasons. Is there a way to tell R to boxplot the whole column 1 and only the first 7 entry for column 2? 回答1: You could simply index the values you want, for example ## dummy version of your data

问题 I'm using ggplot to create sevral boxplots from the following data: df<-(structure(list(Effect2 = c("A2", "A2", "A2", "A2", "A2", "A2", "A2", "A2", "A2", "A2", "A2", "A2", "A2", "A2", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3", "A3",

问题 I would like to compare a set of distributions of scores ( score ), grouped by some categories ( centrality ) and colored by some other ( model ). I've tried the following with seaborn: plt.figure(figsize=(14,6)) seaborn.boxplot(x="centrality", y="score", hue="model", data=data, palette=seaborn.color_palette("husl", len(models) +1)) seaborn.despine(offset=10, trim=True) plt.savefig("/home/i11/staudt/Eval/properties-replication-test.pdf", bbox_inches="tight") There are some problems I have