2个采用Plotly画图的代码： （1）选择适当的数据画一个雷达图；如何动态展示雷达图？ （2）选择适当的数据画一个动态柱状图；如何控制展示的速度？

1. 雷达图动态展示代码：

import plotly.graph_objs as go
import numpy as np
import time

# 随机生成数据
np.random.seed(0)
num_vars = 6
num_points = 10
data = 10 * np.random.rand(num_points, num_vars)

# 绘制雷达图
fig = go.Figure()

for i in range(num_points):
    fig.add_trace(go.Scatterpolar(
        r=data[i],
        theta=[f'var{i+1}' for i in range(num_vars)],
        fill='toself',
        name=f'point{i+1}'
    ))

# 设置布局
fig.update_layout(
    polar=dict(
        radialaxis=dict(
            visible=True,
            range=[0, 10]
        )
    )
)

# 动态展示雷达图
for i in range(num_points):
    fig.data[i].line.color = 'red'
    fig.data[i].marker.color = 'red'
    fig.data[i].marker.size = 10
    fig.data[i].line.width = 2
    fig.show()
    time.sleep(1)

2. 动态柱状图控制展示速度的代码：

import plotly.graph_objs as go
import numpy as np
import time

# 随机生成数据
np.random.seed(0)
num_bars = 6
num_points = 10
data = 10 * np.random.rand(num_points, num_bars)

# 绘制初始柱状图
fig = go.Figure(go.Bar(
    x=[f'point{i+1}' for i in range(num_points)],
    y=data[0],
    name=f'bar1'
))

# 设置布局
fig.update_layout(
    xaxis=dict(title='Point'),
    yaxis=dict(title='Value')
)

# 动态展示柱状图
for i in range(1, num_points):
    fig.add_trace(go.Bar(
        x=[f'point{i+1}' for j in range(num_bars)],
        y=data[i],
        name=f'bar{i+1}'
    ))
    fig.update_traces(marker_color='red', marker_line_width=2, opacity=0.7)
    fig.show()
    time.sleep(1)