Python实现画箱线图展示数据分布情况

        # 创建示例数据
        data = {
            'Group': ['A'] * 11 + ['B'] * 10 + ['C'] * 10,
            'Value': [23, 25, 19, 21, 24, 27, 22, 20, 21, 24, -1, # Group A
                      30, 28, 36, 31, 34, 29, 35, 33, 32, 30,  # Group B
                      15, 17, 14, 16, 13, 18, 14, 15, 17, 16]  # Group C
        }

        # 转换为 DataFrame
        df = pd.DataFrame(data)

        # 设置绘图风格
        sns.set(style="whitegrid")

        # 绘制箱线图
        plt.figure(figsize=(10, 6))
        sns.boxplot(x='Group', y='Value', data=df)

        # 添加标题和标签
        plt.title('Box Plot of Three Groups')
        plt.xlabel('Group')
        plt.ylabel('Value')

        # 显示图表
        # plt.show()
        plt.savefig('./boxPlot_seaborn.png')

        print('自定义箱线图')
        # 示例数据
        data = [
            {'Min': 10, '50%': 50, 'Mean': 55, '95%': 90, '99%': 97, 'Max': 100},
            {'Min': 20, '50%': 60, 'Mean': 65, '95%': 85, '99%': 92, 'Max': 95},
            {'Min': 5, '50%': 40, 'Mean': 45, '95%': 80, '99%': 88, 'Max': 90}
        ]

        # 准备箱线图数据
        box_data = []
        means = []
        positions = []

        for i, d in enumerate(data):
            box_data.append([d['Min'], d['50%'], d['95%'], d['99%'], d['Max']])
            means.append(d['Mean'])
            positions.append(i + 1)

        # 创建图形
        fig, ax = plt.subplots()

        # 绘制箱线图主体
        ax.boxplot(box_data, vert=False, positions=positions, patch_artist=True, showmeans=False,
                   meanline=True, widths=0.6)

        # 添加均值点
        for i, mean in enumerate(means):
            ax.plot(mean, positions[i], 'ro')

        # 设置轴标签
        ax.set_yticks(np.arange(1, len(data) + 1))
        ax.set_yticklabels([f'Data {i + 1}' for i in range(len(data))])

        # 添加标题和标签
        plt.title('Custom Box Plot with Multiple Data Sets')
        plt.xlabel('Value')

        # 显示图形
        plt.show()
        plt.savefig('./boxPlot_auto.png')

        print('自定义箱线图')
        plt.clf()  # 清除当前图形内容
        # 数据
        # Min、50%、Mean、95%、99%、Max
        data = [
            {'data1':[10,50,44,90,97,100]},
            {'data2':[20,60,65,85,92,95]},
            {'data3':[5,40,45,80,88,90]}
        ]

        # 准备箱线图数据
        box_data = [d[list(d.keys())[0]] for d in data]  # 提取数据
        labels = [list(d.keys())[0] for d in data]
        means = [d[list(d.keys())[0]][2] for d in data]


        # 创建图形
        fig, ax = plt.subplots()

        # 绘制箱线图主体
        bp = ax.boxplot(box_data, vert=False,  patch_artist=True, showmeans=True,meanline=True)

        # 添加均值点
        for i, mean in enumerate(means):
            ax.plot(mean, i+1, 'ro')

        # 设置轴标签
        ax.set_yticklabels(labels)

        # 添加标题和标签
        plt.title('Custom Box Plot with Multiple Data Sets')
        plt.xlabel('Value')

        # 显示图形
        # plt.show()
        plt.savefig('./boxPlot_auto.png')