plotly数据科学交互式可视化，Python

Dear 丶 2023-06-23 13:27 6阅读 0赞

plotly和经典Matplotlib最大的不同是plotly可以生成交互式的数据图表。Matplotlib生成的图示静态（死）的图，而plotly是活的图，具体方式是plotly可以生成一个html网页，该网页基于js支持数据交互（点击、缩放、拖拽）等等交互操作。

事先得用Python命令安装：

pip install plotly

Python例子：

import plotly as py
    import plotly.graph_objs as go
    import numpy as np
    
    if __name__ == '__main__':
        count = 20
        x = np.linspace(0, 5, count)  # 随机生成count个0到5之间的数
        y0 = np.random.randn(count) + 8
        print(y0)
        y1 = np.random.randn(count)
        print(y1)
        y2 = np.random.randn(count) - 8
        print(y2)
    
        trace0 = go.Scatter(
            x=x,
            y=y0,
            mode='markers',  # 散点,没有线
            name='散点'  # 曲线名称
        )
    
        trace1 = go.Scatter(
            x=x,
            y=y1,
            mode='lines+markers',  # 散点+线
            name='散点和线',
            marker=dict(
                size=15,  # 点的大小
                color='rgba(255, 180, 190, .6)',  # 颜色。最后一位是透明度
                line=dict(
                    width=2,  # 线的宽度
                    color='rgb(0, 255, 0)'  # 线的颜色
                ))
        )
    
        trace2 = go.Scatter(
            x=x,
            y=y2,
            mode='lines',  # 线
            name='线',
            line=dict(
                width=4,  # 线宽
                color='red'
            )
        )
    
        data = [trace0, trace1, trace2]
        py.offline.plot(data, filename='fig.html')

生成的fig.html图中，交互数据点：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly96aGFuZ3BoaWwuYmxvZy5jc2RuLm5ldA_size_16_color_FFFFFF_t_70][]

原始随机数据：

[ 7.149432    6.50489461  7.16456305  7.45697682  7.36924142  8.87313759
      7.57906709  9.32564909  9.83994729  7.86031166  7.50424235  8.00859527
      8.03884244  8.24660839  7.74482351  7.10029204  7.38240537  8.37656517
     10.25392977  7.69139566]
    [-0.20807945 -1.87541628 -2.1628432   2.02659036 -0.64169184 -0.89742978
     -1.11686915 -0.78583164 -1.60748698 -1.5941247   0.87648078 -0.57077708
      0.09552706 -0.41319839 -0.11193602 -0.51171773  0.20090277 -0.81025678
      0.09127885  0.64375603]
    [ -7.49336588  -7.98602767  -9.99411645 -11.25695211  -8.35283071
      -8.17732449  -7.9029906   -7.01508945  -8.05447955  -9.73398467
      -9.17156658  -7.43255481  -7.68744518  -8.54303014  -7.5810631
      -8.98659986  -8.19372767  -9.24647112  -7.31539077  -9.57868002]

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly96aGFuZ3BoaWwuYmxvZy5jc2RuLm5ldA_size_16_color_FFFFFF_t_70]: https://img-blog.csdnimg.cn/20191219170349288.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly96aGFuZ3BoaWwuYmxvZy5jc2RuLm5ldA==,size_16,color_FFFFFF,t_70