How to graph a function in Python using plotnine library

Question

I've been a longtime R user, recently transitioning over to Python, and I've been trying to carry over my knowledge of plotting with ggplot2, since it is so intuitive. Plotnine is supposedly the most ggplot2-esque plotting library, and I've successfully recreated most graphs with it, except critically how to plot regular functions.

In base R, you can easily define an eq., as in so , input the result into a stat_function() layer, and set the limits of the graph in place of the data arg., and successfully plot a parabola or the like. However, the syntax for setting the graph's limits must be different in Python (perhaps using numpy?), and equations are defined using sympy , which is another divergence for me.

So how would I go about plotting functions with plotnine? The above two hurdles are the two differences with ggplot2 that I think are causing me trouble, since plotnine has so few examples online.

PS This is an example of what I want to recreate in Python using plotnine:

> library(ggplot2)
> basic_plot <- function(x) x^2 + 2.5
> graph <- ggplot(data.frame(x=c(-5,5)), aes(x=x)) +
+ stat_function(fun = basic_plot)
> graph

Answer 1

You do not need numpy, it works just fine the "standard" way! :)

from plotnine import *
import pandas as pd

(ggplot(pd.DataFrame(data={"x": [-5, 5]}), aes(x="x"))
    + stat_function(fun=lambda x: x**2+2.5))

Answer 2

One of the main differences that caused me problems was the same as posted in the question. Specifically:

in R aes(x = x) or aes(x)

in plotnine aes(x = 'x')