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Python in Digital Scholarship

This guide will provide an introduction to using Python in research and instruction and what resources are available in the Freedman Center.

Exploratory Data Analysis Tutorials

DataCamp – Exploratory Data Analysis in Python

A step-by-step tutorial introducing key EDA concepts using Python. Covers summary statistics, data visualization, and best practices. Suitable for beginners and includes practical examples with Pandas and Seaborn.

DigitalOcean – Exploratory Data Analysis in Python

A detailed walkthrough of EDA techniques using Python, Pandas, and Matplotlib. Emphasizes data cleaning, transformation, and basic visualization. Well-suited for readers familiar with basic Python syntax.

freeCodeCamp – Learn Python for Data Science with Hands-On EDA Projects

An applied guide that introduces EDA through real-world data science projects. Integrates statistical analysis, A/B testing, and business intelligence use cases. Ideal for learners seeking a project-based approach.

LearnPython.com – Python EDA Cheat Sheet

A concise reference sheet summarizing common EDA techniques in Python. Includes code examples for data inspection, visualization, and correlation analysis. Useful as a quick guide for beginners or review for intermediate users.