请问python应该如何画这种图？

Question

就是这种形式的图，我现在有几组数据A、B、C，每组数据有两个中心点core1和core2，中心点core1对应一组置信区间的上界up1和下界down1，中心点core2有一组置信区间的上界up2和下界down2。
也就是说，数据长这样：
A：core1, up1, down1, core2, up2, down2
B：core1, up1, down1, core2, up2, down2
C：core1, up1, down1, core2, up2, down2

然后我想要画成种图，就用一张图表示，不用两个子图，应该如何画呢？

Answer 1

https://matplotlib.net/stable/gallery/statistics/errorbar_lim...

https://matplotlib.net/stable/gallery/statistics/errorbar_fea...

在示例里挑个类似的. 实在不行, 就自己用 matplot 的 Line 对象往figure上加元素.
plt.subplots(1, 2) 这是一个一行2列的图

Answer 2

研究了一上午弄出来了，绘图结果如下：

表格数据如下：

绘画的代码如下，我懒得整理了，所以比较凌乱，看看就好

import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib as mpl
mpl.rc("font",family='MicroSoft YaHei',weight="bold")

def draw_errorbar(ax):
    capsize = .2
    at_group = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8])
    mew = 2.0250000000000004
    markersize = 45.80442088933919
    kws = {'lw': 2.7}

    confint = confints1.to_numpy()
    colors=[(0.12156862745098039, 0.4666666666666667, 0.7058823529411765)] * 9


    for at, (ci_low, ci_high), color in zip(at_group,
                                            confint,
                                            colors):
        ax.plot([at, at], [ci_low, ci_high], color=color, **kws)
        ax.plot([at - capsize / 2, at + capsize / 2],
                [ci_low, ci_low], color=color, **kws)
        ax.plot([at - capsize / 2, at + capsize / 2],
                [ci_high, ci_high], color=color, **kws)

    ax.scatter(at_group, df['cent'][:9], linewidth=mew, marker='o', s=markersize, label='A')

    offset = 0.2
    at_group = at_group + offset
    confint = confints2.to_numpy()
    colors=[(1.0, 0.4980392156862745, 0.054901960784313725)] * 9
    for at, (ci_low, ci_high), color in zip(at_group,
                                            confint,
                                            colors):
        ax.plot([at, at], [ci_low, ci_high], color=color, **kws)
        ax.plot([at - capsize / 2, at + capsize / 2],
                [ci_low, ci_low], color=color, **kws)
        ax.plot([at - capsize / 2, at + capsize / 2],
                [ci_high, ci_high], color=color, **kws)

    ax.scatter(at_group, df['cent'][9:], linewidth=mew, marker='o', s=markersize, label='B')

    ax.set_ylabel('ylabel', fontdict={'fontsize': 12, 'font': 'MicroSoft YaHei'})
    ax.set_xticks(np.arange(9) + offset / 2)
    ax.set_xticklabels(df['name'][:9])
    ax.legend(loc='best', title='')

    ax.axvspan(0.6, 2.6, facecolor='#F3F7FA', zorder=0)
    ax.axvspan(2.6, 6.6, facecolor='#F0E9E1', zorder=0)
    ax.axvspan(6.6, 8.6, facecolor='#E7F2EC', zorder=0)
    ax.axhline(0, color='#000', linestyle=':', zorder=0)


plt.figure(figsize=(12, 6))
ax = plt.gca()
draw_errorbar(ax)
plt.savefig('t.pdf')