Running through the examples in Gelman and Hill's Data Analysis Using Regression and Multilevel/Hierarchical Models in both R and Python using IPython/Jupyter notebooks. To make the most of the code you need a copy of the book-- buy one or get a copy from the library. The websites for the book and data/code are:
If you'd like to use the IPython notebooks, just grab them and compute away. Of course, relevant Python and R packages will need to be installed for the notebooks to work on your local machine.
If you'd like to start with the R-markdown (.Rmd) and markdown (.md) files, those are available as well. Notes on how to turn these into the IPython notebooks (.ipynb) are given below. These use the Python package notedown to do the conversions.
Python: md to ipynb
notedown chptr2.3.md > chptr2.3.ipynbR: Rmd to ipynb
I add the -R.ipynb ending for notebooks running R code using rpy2.
notedown chptr2.3.Rmd --knit --rmagic > chptr2.3-R.ipynb