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[vincentarelbundock]

import polars as pl
import numpy as np
import statsmodels.formula.api as smf
from marginaleffects import *

mtcars = pl.read_csv("https://vincentarelbundock.github.io/Rdatasets/csv/datasets/mtcars.csv")

mod = smf.ols("mpg ~ hp * wt * am", data = mtcars).fit()
cond = {
  "hp": None,
  "wt": [mtcars["wt"].mean() - mtcars["wt"].std(),
         mtcars["wt"].mean(),
         mtcars["wt"].mean() + mtcars["wt"].std()],
  "am": None
}
p = plot_predictions(mod, condition = cond)