Exploratory Data Analysis Workshop

Workshop materials for learning exploratory data analysis techniques using Python and Jupyter notebooks.

Workshop Materials

Download slides and sample data for this workshop.

Slides
📊 PowerPoint 📄 PDF
Sample Dataset
📊 data.csv

Workshop Exercises

Hands-on exercises for learning exploratory data analysis techniques.

Materials
📓 Exercise Notebook

Python 3 is required to run this notebook. We recommend using venv to create a virtual environment.

This notebook uses common data analysis libraries including pandas, numpy, matplotlib, and seaborn.

Create Virtual Environment and Install Dependencies
python3 -m venv venv
source venv/bin/activate
pip install jupyter pandas numpy matplotlib seaborn
Run the Notebook
jupyter notebook

Instructor Version

Complete notebook with solutions for instructors.

Materials
📓 Instructor Notebook

R Version

Workshop materials for R users.

Materials
📊 R Code (HTML) 📝 R Markdown Source

R and RStudio are recommended for working with R Markdown files.

Install Required Packages
install.packages(c("tidyverse", "ggplot2", "dplyr"))
Open R Markdown File

Open RCode.Rmd in RStudio and click "Knit" to render the document.

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