This week, I had the opportunity to create the foundation of my first R package as part of Module #10 in Dr. Friedman’s class. The assignment focused on understanding the structure of an R package and writing a complete DESCRIPTION file—an essential component that documents a package’s metadata and dependencies.

I named the package Friedman, following the template provided. My package is designed to support users in performing basic data visualization and analysis tasks, inspired by the core lessons we’ve learned using tools like ggplot2 and plyr. The idea is to eventually include a small set of reusable functions that simplify data exploration for students, analysts, and anyone working with tabular data.

Please 📂Check out my complete code on GitHub!

The file includes basic fields such as the package title, version number, author information, description, and dependencies. I chose the CC0 license to make the work publicly available and modifiable so others can adapt it freely.

Possible Final Project Directions

While I haven’t decided on the final functions I’ll include in the package yet, I’ve been brainstorming a few directions. Over the next week, I plan to explore and narrow it down based on feasibility and usefulness. Here are three potential ideas:

1. Wildfire Data Toolkit – Functions to analyze and visualize wildfire damage in California or other states. I could include tools to summarize cost by year, map fire locations, and flag the most destructive incidents.
2. Exploratory Data Helpers – A set of utility functions to quickly summarize datasets, including column types, missing values, outlier detection, and variable correlations. This would help students or analysts do fast, repeatable EDA.
3. Plot Customizer – Wrappers around ggplot2 for creating polished visualizations (bar plots, scatter plots, etc.) with preset themes, colors, and labels, especially helpful for those new to data visualization.

No matter which route I take, I want the package to be beginner-friendly, well-documented, and practical for real-world data scenarios.

You can find my package in progress on GitHub here: SAM_r_Repo

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