11 comments

[ 2.9 ms ] story [ 33.2 ms ] thread
I wish they had more examples for time-series data.
Seems like a fair amount of boilerplate. You really have to specify that the axes are Cartesian with every simple two-axis plot you make?
Half of my plots use logarithmic scale. Makes sense to me.

I really like the default axis styling where they have gone against the mainstream style of gnuplot/matlab. I'm definitely going to try this out sometime soon.

This is the code from the beginning of the tutorial:

    # make some test data
    import numpy
    x = numpy.linspace(0, 10)
    y = x ** 2
    
    # plot it
    import toyplot
    canvas = toyplot.Canvas(width=300, height=300)
    axes = canvas.cartesian()
    mark = axes.plot(x, y)
3 lines excluding the import doesn't strike me as a remarkable amount of boilerplate
Seems like an easy thing to make a helper function for.
Am I the only one who gets a bit ticked off when seeing the axis not cross at the origin ?
(comment deleted)
Is that a style decision? I haven't seen that before. Seems confusing.
are there any significant benefits over matplotlib?