This of course works with other symbolic manipulation:
plot(sin(x).diff())
plot(sin(x).subs(x, x**2))My use case is not a scratch pad with one plotting window; it’s dozens of windows with regressions and stuff. Each window is a completely different context; some of them are short lived and some of them are used for weeks. Using as many notebooks is very impractical. For example, seeing where one parameter is going in one calculations is trivial and quicker than starting a notebook and setting it up. Works transparently over ssh, too.
I am more or less fluent in Matplotlib, because I work with people who use it and I need to understand whatever the students are doing (and some of them use Python and some use R, which is a whole other discussion). I just dislike it and don’t use it much for my things. Ultimately, gnuplot’s syntax for regression and complex plots is much more concise.
I any case I think it’s good intellectual hygiene to use several tools regularly, lest you end up stuck in a way of thinking, so I encourage students to try others. It’s also good to have discussions about these things that don’t end up in holy wars; we need to be curious.
import sympy
sympy.plot(sympy.sin(x))
from sympy import *
x = symbols('x')
plot(sin(x))
You just want to plot the sine function, but first you have to import libraries, declare symbols (with a scary correspondence between strings and variable names), and finally plot the damn function.
Edit: plus, if I'm plotting with Sympy it's almost certainly something I've calculated symbolically with Sympy, so everything is defined and ready, and it's much more elegant than switching to a separate program. For a one-off "what does function look like?" question, both these tools are far too clunky, and I'd use Desmos or GeoGebra.
Sympy is just a Python library, and one of the types it defines is symbolic maths variables, so you define Python variables just like with any other library, and then use them.
And this, my friends, is why mathematicians will never feel at home using Python+libraries. Instead of having a programming environment ideally suited to the needs of math, you need to fit your math to the Procrustean bed of Python syntax.