For even the simplest possible plot, I have to create a subplot and axis.
Sometimes I'd like to just plot a function. I don't want to initialize arrays for that.
It's easy to forget that I have to `import matplotlib.pyplot`
I don't need to plot things often, but whenever I use matplotlib, I always have to spend a few minutes to look up how to use it.
So? Can't that be abstracted away once in a custom lib, of the 3-4 plots you use 99% of the time, and be done with it?
In which case, you just need to pass in your data and labels, in a specific format, and that's it.
This does not beat gnuplot's simplicity where you don't even need to define that.
The following line is a complete gnuplot program to plot the sine function:
plot sin(x)
Yeah, and that's really not helpful for sharing code or doing exploratory charting. It's never, ever as simple as just "being done with it".
vega-lite-api is my charting library of choice these days. Much simpler than gnuplot, d3, matplotlib, etc.
x = np.arange(0, 10, 0.01)
pb.plot(x, np.sin(x)
pb.show()
what do you mean hard?
A minor headache is when you have to break out of Pyplot to use some of the more detailed behaviors of Matplotlib, and now you're interacting with both Pyplot and the lower level calls. For instance, plt.title('foo') and gca().set_title('foo') do the same thing.
If you're a fluent programmer, you fly past those seeming inconsistencies with barely any notice. Explaining them to a novice programmer is harder.