import random fig = plt.figure(figsize=(13,13)) ax = fig.add_subplot(111,projection='3d') colors = ['r', 'g', 'b', 'c', 'm'] for i in new_df.index: ax.scatter(new_df.loc[i,'Total Cases'],new_df.loc[i,'Total Deaths'],new_df.loc[i,'Total Recovered'],c=random.choice(colors)) ax.text(new_df.loc[i,'Total Cases'],new_df.loc[i,'Total Deaths'],new_df.loc[i,'Total Recovered'], new_df.loc[i,'Country/Region'], fontsize=10) # 设置刻度 ax.set_xlim([0,new_df['Total Cases'].max() + 1]) ax.set_ylim([0,new_df['Total Deaths'].max() + 1]) ax.set_zlim([0,new_df['Total Recovered'].max() + 1]) # 设置坐标轴标签 ax.set_xlabel('Total Cases',fontsize=15) ax.set_ylabel('Total Deaths',fontsize=15) ax.set_zlabel('Total Recovered',fontsize=15) ax.set_title('3D scatterplot',fontsize=25) plt.show()这段代码无法运行

这段代码无法运行可能是因为缺少必要的模块和变量，需要先导入相关的库和数据集，才能正确运行。以下是一个示例代码，您可以根据自己的需要进行修改和调整：

import pandas as pd
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import random

# 导入数据集
df = pd.read_csv('covid19_data.csv')

# 对数据进行处理
new_df = df.groupby(['Country/Region']).sum().reset_index()

# 创建3D散点图
fig = plt.figure(figsize=(13,13))
ax = fig.add_subplot(111,projection='3d')

# 绘制散点图并添加文本标注
colors = ['r', 'g', 'b', 'c', 'm']
for i in new_df.index:
    ax.scatter(new_df.loc[i,'Total Cases'],new_df.loc[i,'Total Deaths'],new_df.loc[i,'Total Recovered'],c=random.choice(colors))
    ax.text(new_df.loc[i,'Total Cases'],new_df.loc[i,'Total Deaths'],new_df.loc[i,'Total Recovered'], new_df.loc[i,'Country/Region'], fontsize=10)

# 设置刻度
ax.set_xlim([0,new_df['Total Cases'].max() + 1])
ax.set_ylim([0,new_df['Total Deaths'].max() + 1])
ax.set_zlim([0,new_df['Total Recovered'].max() + 1])

# 设置坐标轴标签
ax.set_xlabel('Total Cases',fontsize=15)
ax.set_ylabel('Total Deaths',fontsize=15)
ax.set_zlabel('Total Recovered',fontsize=15)

ax.set_title('3D scatterplot',fontsize=25)

plt.show()

请确保您已经正确导入了相关的库和数据集，并将数据集命名为'covid19_data.csv'，否则会导致代码无法运行。