# Exploratory Data Analysis: A Reproducible Notebook Template

**Daniel Ari Friedman** (2026) · *Zenodo*

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.21086292.svg)](https://doi.org/10.5281/zenodo.21086292)

---

## Abstract

Exploratory data analysis (EDA) is the most common entry point in applied
research, yet it is also where reproducibility most often breaks down: logic
accumulates in notebook cells that are never tested and quietly drift from the
prose describing them. This paper presents the computational-notebook
exemplar of the Research Project Template (https://github.com/docxology/template):
an interactive walkthrough notebook
(projects/templates/template_eda_notebook/notebooks/eda_walkthrough.ipynb)
that imports a small, fully-tested EDA library rather than carrying logic in its
cells.

We ship a deterministic dataset (data/measurements.csv) with a designed
correlation structure and a handful of missing values, then load, clean,
summarize, correlate, and visualize it entirely through tested functions in
src/eda/. The library is side-effect-free — no plotting and no file I/O — and
standalone (numpy and pandas only), so it is covered above the 90% project gate
and reused identically from the notebook, the thin analysis script
(scripts/eda_analysis.py), and this manuscript.

Contributions are methodological and architectural. On the methods side,
we walk the canonical first EDA pass: surface missingness explicitly rather than
imputing it, compute per-column descriptive statistics and per-group means, and
rank features by Pearson correlation. On the architecture side, we demonstrate
the notebook-to-tested-source extraction workflow — explore fast in a cell, and
the moment a computation matters, move it into the library behind a failing
test — verified by a zero-mock suite and a structural notebook-binding check
().

---
Associated artifacts
GitHub release: v1.0.0 (https://github.com/docxology/template_eda_notebook/releases/tag/v1.0.0)
DOI: https://doi.org/10.5281/zenodo.21086292
Zenodo: https://zenodo.org/records/21086292
PDF SHA-256: 0b10852bda89361cd71063867b55d9aed942881476867813facd549a961b0c1d

## Keywords

exploratory data analysis · computational notebook · reproducible research · pandas · data cleaning · correlation analysis

## Publication Details

| Field | Value |
|------|-------|
| **DOI** | [10.5281/zenodo.21086292](https://doi.org/10.5281/zenodo.21086292) |
| **Published** | 2026 |
| **Version** | 1.0.0 |
| **Zenodo record** | https://zenodo.org/records/21086292 |
| **GitHub release** | https://github.com/docxology/template_eda_notebook/releases/tag/v1.0.0 |
| **Source repository** | https://github.com/docxology/template_eda_notebook |

## Files

- `Friedman_2026_Exploratory_0b10852b.pdf` - Zenodo PDF

## Citation

> Friedman, D. A. (2026). *Exploratory Data Analysis: A Reproducible Notebook Template*. Zenodo. https://doi.org/10.5281/zenodo.21086292

## Related

- Zenodo record: https://zenodo.org/records/21086292
- GitHub release: https://github.com/docxology/template_eda_notebook/releases/tag/v1.0.0
- Source repository: https://github.com/docxology/template_eda_notebook
- [Full Bibliography](../../pages/BIBLIOGRAPHY.md) · [All Papers](../README.md)