Above image was generated by the following code:
import numpy as np from bokeh.plotting import figure, output_file, show # prepare some data 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) ] # output to static HTML file (with CDN resources) output_file("color_scatter.html", title="color_scatter.py example", mode="cdn") TOOLS="resize,crosshair,pan,wheel_zoom,box_zoom,reset,box_select,lasso_select" # create a new plot with the tools above, and explicit ranges p = figure(tools=TOOLS, x_range=(0,100), y_range=(0,100)) # add a circle renderer with vectorized colors and sizes p.circle(x,y, radius=radii, fill_color=colors, fill_alpha=0.6, line_color=None) # show the results show(p)
Thanks to Bokeh library. Wow!
Above example was taken from Bokeh quickstart
Yup - I got new friend. Plotting with Bokeh looks very interesting in terms of visualizing huge, browsable dataset.