Matplotlib绘制箱线图及标注特征点

效果图

获取箱线图特征值代码

class Tool:

    def boxFeature(self,bp):
        """获取箱体图特征
        【输入】 bp boxplot返回的字典对象
        【输出】 llim, q1, q2, q3, ulim
        """

        (x_q1, y_q1), (x_llim, y_ulim) = bp['whiskers'][0].get_xydata()  # 下四分位数
        (x_q3, y_q3), (x_ulim, y_llim) = bp['whiskers'][1].get_xydata()  # 上四分位数

        (x_left_low, y_llim), (x_right_up, y_llim) = bp['caps'][0].get_xydata()  # 下限 非异常范围内的最小值
        (x_left_up, y_ulim), (x_right_low, y_ulim) = bp['caps'][1].get_xydata()  # 上限 非异常范围内的最大值

        (x_left_median, y_q2), (x_right_median, y_q2) = bp['medians'][0].get_xydata()  # 中位数

        return y_llim, y_q1, y_q2, y_q3, y_ulim

绘制箱线图代码

    rain_cins, unrain_cins, = rainSet['cins'], unrainSet['cins'].dropna()

    tool = Tool()

    fig, ax = plt.subplots(nrows=1, ncols=2)
    #labels must be a list,or going wrong
    bp1= ax[0].boxplot(rain_cins,labels = ['rain'],sym='r')
    ax[0].set_title('cins of boxplot', fontsize=20)  # 标题，并设定字号大小

    bp2= ax[1].boxplot(unrain_cins, labels=['unrain'], sym='r')
    ax[1].set_title('cins of boxplot', fontsize=20)  
    
     # 获取特征值
    llim_ax0, q1_ax0, q2_ax0, q3_ax0, ulim_ax0=tool.boxFeature(bp1)
    llim_ax1, q1_ax1, q2_ax1, q3_ax1, ulim_ax1=tool.boxFeature(bp2)
    
    # ax0添加标签
    ax[0].text(1.2, llim_ax0, '%.2f' % llim_ax0, verticalalignment='center',  fontsize=10, backgroundcolor="white")
    ax[0].text(1.2, q1_ax0, '%.2f' % q1_ax0, verticalalignment='center',  fontsize=10, backgroundcolor="white")
    ax[0].text(1.2, q2_ax0, '%.2f' % q2_ax0, verticalalignment='center',  fontsize=10, backgroundcolor="white")
    ax[0].text(1.2, q3_ax0, '%.2f' % q3_ax0, verticalalignment='center',  fontsize=10, backgroundcolor="white")
    ax[0].text(1.2, ulim_ax0, '%.2f' % ulim_ax0, verticalalignment='center',  fontsize=10, backgroundcolor="white")

    # ax1添加标签
    ax[1].text(1.2, llim_ax1, '%.2f' % llim_ax1, verticalalignment='center',  fontsize=10, backgroundcolor="white")
    ax[1].text(1.2, q1_ax1,   '%.2f' % q1_ax1,  verticalalignment='center',  fontsize=10, backgroundcolor="white")
    ax[1].text(1.2, q2_ax1-1, '%.2f' % q2_ax1,  verticalalignment='center',  fontsize=10, backgroundcolor="white")
    ax[1].text(1.2, q3_ax1+0.5,   '%.2f' % q3_ax1,  verticalalignment='center',  fontsize=10, backgroundcolor="white")
    ax[1].text(1.2, ulim_ax1, '%.2f' % ulim_ax1, verticalalignment='center',  fontsize=10, backgroundcolor="white")

   # 显示图像
    plt.show()