Python数据分析及可视化实例之Bokeh与Jupyter生成可视化图表

发布时间:2021-12-03 公开文章

Talk is cheap , show U the code.

 

通用图表直接重构官方文档中的chart图表代码,

和Pandas、Flask无缝衔接,不能再炫酷的D3.js

在Jupyter中体验一下Bokeh的便捷

import numpy as np
from bokeh.plotting import figure
N = 4000
x = np.random.random(size=N) * 100
y = np.random.random(size=N) * 100
radii = np.random.random(size=N) * 1.5
colors = [
    "#%02x%02x%02x" % (int(r), int(g), 150) for r, g in zip(50+2*x, 30+2*y)
]
TOOLS="hover,crosshair,pan,wheel_zoom,zoom_in,zoom_out,box_zoom,undo,redo,reset,tap,save,box_select,poly_select,lasso_select,"
p = figure(tools=TOOLS)
p.scatter(x, y, radius=radii,
          fill_color=colors, fill_alpha=0.6,
          line_color=None)

 

 

 

 

还可以做出这样的图: