Boxplot for multiple categorical data sets. Learn more about boxplot, multiple boxplots, categorical plots
## [1] plot.acf* plot.data.frame* plot.decomposed.ts* ## [4] plot.default plot.dendrogram* plot.density* ## [7] plot.ecdf plot.factor* plot.formula* ## [10] plot.function plot.hclust* plot.histogram* ## [13] plot.HoltWinters* plot.isoreg* plot.lm* ## [16] plot.medpolish*...
box=plt.boxplot(x=[np.random.normal(size=500),np.random.normal(size=1000)],patch_artist=True,labels=['sampleA','sampleB'])colors=['lightblue','lightgreen']forpatch,colorinzip(box['boxes'],colors):patch.set_color(color) 输出结果如下 boxplot的返回值是一个字典,包括了箱体图中的各个元素...
1,100)foriinrange(1,4)}# 创建图形和坐标轴fig,ax=plt.subplots()# 绘制箱线图ax.boxplot(data.values())# 设置标题和标签ax.set_title('Boxplot with Dictionary - how2matplotlib.com')ax.set_xlabel('Groups')ax.set_ylabel('Values')ax.set_xticklabels(data.keys())# 显示图形plt.show...
boxplot10 本部分主要基于我的Python for Data Visualization课程的免费预览视频。在上一节中,我们介绍了正态分布的箱线图,但是由于您显然并不总是具有基本的正态分布,因此让我们研究一下如何在真实数据集上利用箱形图。为此,我们将利用乳腺癌威斯康星州(诊断)数据集. ...
4)] # 创建新的图形对象 fig = plt.figure() # 设置图形的位置和尺寸 fig.subplots_adjust(hspace=0.5) # 循环绘制多个boxplot for i, d in enumerate(data): # 创建子图 ax = fig.add_subplot(len(data), 1, i+1) # 绘制boxplot ax.boxplot(d) # 设置子图标题 ax.set_title(f"Boxplot {i...
sns.boxplot( x=df["species"], y=df["sepal_length"] ); 1. 2. 3. 4. # 多个数值变量 Several numerical variable # 可以研究几个数值变量的分布,比如说萼片的长度和宽度: sns.boxplot(data=df.iloc[:,0:2]); 1. 2. 3. # 水平箱型图 Horizontal boxplot with seaborn ...
The box plot, also known as the whisker plot, box-and-whisker plot, or box-and-line plot, gets its name from its box-like appearance. This statistical chart is used to display the distribution of a set of continuous data. For example, you can use the box plot to analyze the score ...
().setValue(0) elif key == 16777234: # # Ctrl+ left 滑动条位置回到左端 if event.modifiers() & Qt.ControlModifier:#Ctrl 键被按下 self.horizontalScrollBar().setValue(0) else: QWidget.keyPressEvent(self, event) def randomData(self): from random import random for i in range(0,100):...
bh=boxplot(x, {g2,g1},'notch','on','whisker',1,'colorgroup',g1, 'factorgap',[8 1],'symbol','.','outliersize',4,'widths',0.6,'positions',positions) xlabel('Training data size'); ylabel('Mean zero-one error') grid on set(gca,'YLim',[0.45,0.85],'gridLineStyle', '-.'...