下面的代碼創建一個分類圖，其頂部有一個點圖，其中點圖顯示每個類別的平均值和 95% 置信區間。我需要將平均數據標簽添加到圖中，但我不知道該怎么做。僅供參考，每個類別都有數千個點，因此我不想標記每個數據點，而只想標記estimator=np.mean點圖中的值。這可能嗎？？我在此處創建了一個示例數據集，以便您可以復制并粘貼代碼并自行運行。import pandas as pdimport seaborn as snsimport matplotlib.pyplot as pltimport matplotlib.ticker as mtickimport numpy as npd = {'SurfaceVersion': ['v1', 'v1', 'v1', 'v2', 'v2', 'v2', 'v3', 'v3', 'v3'],        'Error%': [.01, .03, .15, .28, .39, .01, .01, .06, .09]}df_comb =  pd.DataFrame(data=d)plotHeight = 10plotAspect = 2 #create catplot with jitter per surface version:ax = sns.catplot(data=df_comb, x='SurfaceVersion', y='Error%', jitter=True, legend=False, zorder=1, height=plotHeight, aspect=plotAspect)ax = sns.pointplot(data=df_comb, x='SurfaceVersion', y='Error%', estimator=np.mean, ci=95, capsize=.1, errwidth=1, hue='SurfaceVersion', color='k',zorder=2, height=plotHeight, aspect=plotAspect, join=False)ax.yaxis.set_major_formatter(mtick.PercentFormatter(xmax=1.0))plt.gca().legend().set_title('')plt.grid(color='grey', which='major', axis='y', linestyle='--')plt.xlabel('Surface Version')plt.ylabel('Error %')plt.subplots_adjust(top=0.95, left=.05)plt.suptitle('Error%')plt.legend([],[], frameon=False)                #This is to get rid of the legend that pops up with the seaborn plot b/c it's buggy.plt.axhline(y=0, color='r', linestyle='--')plt.show()