StatWrap 0.2.16

A package for people new to statistics and Python.

StatWrap

This is a package meant for intro stats students who are also new to Python, or at least its statistical libraries.

Different submodules adopt different conventions. The fpp submodule corresponds to Statistics by Freedman, Pisani, and Purves. The sheets module corresponds to Google Sheets.

IPython Usage

The target user will use this package in a Google Colab or Jupyter notebook. Install with !pip install statwrap.

Then import the package and use a magic command to load the desired module.

import statwrap
%use_fpp

%use_fpp imports the functions that adhere to the conventions of Freedman, Pisani, and Purves. This will also overwrite and introduce new pandas methods for working with DataFrames and Series. %use_sheets is similar, but it borrows the conventions of Google Sheets.

Design and Style

Python is known for its simplicity and readability. Still, someone new to statistics and programming might find themselves intimidated by the many imports necessary to work with data and run statistical tests. A user will find conflicting defaults across different packages and terminology can differ. This package aims to reduce the mental overhead required to juggle the notation they find in a textbook with formula names in Google Sheets and what they find in packages like NumPy, pandas, scipy, and statsmodels.

The design principles of this package are mostly the design principles of Python. However, we don't always adhere to the principle that "explicit is better than implicit" and we prefer convention to configuration, with the configuration being done once with a magic command like %use_fpp.

If you are interested in using this in your classroom or contributing, please reach out to me at [e-mail].