将鼠标悬停在数据点上时的 3D Matplotlib 散点图标签

Question

我一般来说是 matplotlib/python 的新手，并使用 matplotlib 创建了一个简单的 3d 散点图。我能够生成散点图，但现在我希望当鼠标悬停在每个点上时显示每个点的名称。这些名称将来自我正在使用的数据集：

df 是数据框

z = df['est_diameter_max']
x = df['miss_distance']
y = df['relative_velocity']
n = df['name']


fig = plt.figure(figsize = (20,17))
ax = plt.axes(projection ="3d")

ax.xaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))
ax.yaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))
ax.zaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))

ax.xaxis.line.set_color("red")
ax.yaxis.line.set_color("green")
ax.zaxis.line.set_color("white")

ax.tick_params(axis='x', colors='red')  # only affects
ax.tick_params(axis='y', colors='green')  # tick labels
ax.tick_params(axis='z', colors='white')  # not tick marks

ax.scatter3D(x, y, z, color = "white")
ax.set_facecolor("black")

plt.title("Hazardous Near Earth Objects that Missed (2020-2022)", fontweight ='bold')
ax.set_xlabel('Missed Distance in KM', fontweight ='bold', color='red') 
ax.set_ylabel('Velocity Relative to Earth', fontweight ='bold', color='green') 
ax.set_zlabel('Estimate Max Diameter in KM', fontweight ='bold', color='white')

plt.show()

我可以在网上找到的任何代码，但它要么什么也不做，要么给我提供我不理解的错误消息。我担心这超出了我的能力，但我想如果向我解释一下我就能理解。

Answer 1

试试这个（从如何向绘图添加悬停注释借用了一些代码）：

import pandas as pd

import matplotlib.pyplot as plt

def update_annot(ind):
    
    pos = sc.get_offsets()[ind["ind"][0]]
    annot.xy = pos
    text = "{}".format(" ".join([data[n][3] for n in ind["ind"]]))
    annot.set_text(text)
    annot.get_bbox_patch().set_alpha(0.4)
    
def on_plot_hover(event):
    if event.inaxes == ax:
        cont, ind = sc.contains(event)
        if cont:
            update_annot(ind)
            annot.set_visible(True)
            fig.canvas.draw_idle()
        else:
            annot.set_visible(False)
            fig.canvas.draw_idle()
    

data = [
        [123, 456, 78, 'larry'],
        [321, 654., 87, 'moe'],
        [111, 222, 33, 'curly']
        ]
df = pd.DataFrame(data, columns=['est_diameter_max','miss_distance','relative_velocity','name'])


z = df['est_diameter_max']
x = df['miss_distance']
y = df['relative_velocity']
n = df['name']


fig = plt.figure(figsize = (20,17))
ax = plt.axes(projection ="3d")

ax.xaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))
ax.yaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))
ax.zaxis.set_pane_color((0.0, 0.0, 0.0, 0.0))

ax.xaxis.line.set_color("red")
ax.yaxis.line.set_color("green")
ax.zaxis.line.set_color("white")

ax.tick_params(axis='x', colors='red')  # only affects
ax.tick_params(axis='y', colors='green')  # tick labels
ax.tick_params(axis='z', colors='white')  # not tick marks

sc = ax.scatter3D(x, y, z, color = "white", label='my data')
ax.set_facecolor("black")

plt.title("Hazardous Near Earth Objects that Missed (2020-2022)", fontweight ='bold')
ax.set_xlabel('Missed Distance in KM', fontweight ='bold', color='red') 
ax.set_ylabel('Velocity Relative to Earth', fontweight ='bold', color='green') 
ax.set_zlabel('Estimate Max Diameter in KM', fontweight ='bold', color='white')

fig.canvas.mpl_connect('motion_notify_event', on_plot_hover)

annot = ax.annotate("", xy=(0,0), xytext=(20,20),textcoords="offset points",
                    bbox=dict(boxstyle="round", fc="w"),
                    arrowprops=dict(arrowstyle="->"))
annot.set_visible(False)


plt.show()