My projects

Projects overview

These projects utilize HTML, CSS, Python, and JavaScript.

HTML, CSS, and JavaScript are utilized in the first 3 projects on the list.
HTML and CSS are used for basic functionality of the site, as well as the general style and themes of the sites.

JavaScript is relied upon in the first project, especially. It aims to display a firm understanding of JavaScript, using features such as arrays, modifying the Document Object Model in real-time, as well as enhanced functionality of buttons and links on the pages.

Python, Matplotlib, and Seaborn are utilized in the final project on the list, which was a quick study of Python and an inspection of Data Analysis in a self-led format.

Project Descriptions

Pokemon Type Quiz: My latest project, utilizing HTML, CSS and JavaScript functionality. It is an in-browser quiz app, in which once you begin the quiz, you are prompted with 8 questions about Pokemon type matchups; with each selection, user is prompted with a dialogue box showing whether they were correct, or incorrect. Upon quiz completion, user is shown a score of how many were correct out of 8, and prompted to re-take the quiz.

The Pokeroute Project: This project is still a work in progress, utilizing HTML, CSS, and JavaScript. I aim to, once complete, have an easily navigateable site which each page will display a map of each Pokemon region respectively, upon which you can hover on certain regions of the map and it will show the available items/Pokemon for such areas. I aim to implement a "to-do" list of sorts, where you can make a goal of certain items or Pokemon you aim to receive.

Personal Site: This is the site you're on right now! Utilizes HTML and CSS, at the moment with updates to come. Aim to show technological literacy, along with highlighting marketable skills and previous work experience in a resume like format, accessible through a personal site.

Heavy Burdens: This was my first, and as of right now only, Data Analysis project. It is an interest of mine because I have always personally hypothesized that low-income living, and obesity, go hand in hand. Upon examining the stats on these certain factors, my hypothesis ended up being correct. I used tools such as Matplotlib and Seaborn to turn the information to a graph, and utilized google sheets and Python to clean the data, removing information that wasn't needed, as well as implementing it into code to present the information in an easily readable and understandable format.