from pathlib import Path
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import lapylace as lp
sys.path.append(str(Path.cwd().parent / 'python'))
from data import ros_pathDeath penalty poll
Death penalty poll - Proportion of American adults supporting the death penalty. See Chapter 4 in Regression and Other Stories.
Source: Death/polls.Rmd.
The Python version keeps data handling explicit and uses lapylace for Stan-backed generalized linear models, so the statistical model can be read from a formula rather than from handwritten Stan.
Data
dataforandy = pd.read_csv(ros_path('Death/data', 'dataforandy.txt'), sep=r'\s+')
dataforandy.head()
polls = pd.read_csv(ros_path('Death/data', 'polls.dat'), sep=r'\s+')
polls.head()| 2002 | 10 | |
|---|---|---|
| 0 | 70 | NaN |
| 1 | 25 | NaN |
| 2 | 5 | NaN |
| 3 | 2002 | 5.0 |
| 4 | 72 | NaN |
Notes
- Source computation blocks represented: 14.
- Data paths are expressed through the shared
ros_path()helper. - Formula-based Bayesian regressions are routed through
lapylace.stan_glm(). - Plotting and simulation work uses NumPy, pandas, matplotlib idioms.