I'm Tom. A few of years ago, I taught myself python to better understand and visualize the data I was working with. Next thing I knew, I was hooked on coding.
Today I constantly find myself coming up with challenging new projects that combine my love for coding, sports, and history.
I am a self-taught coder with a background in communications always on the look out for new ways to convey the stories behind the numbers.
I have experience in data analytics, web applications development, natural language processing, data visualization, and database systems & information modeling.
Take a look at some of my projects, along with my repos on Github.
Below are a few of my projects. I am always looking for new data visualization projects. Data helps us to appreciate the similarities and differences between places, eras, peoples, etc. Perhaps most importantly it helps us to understand and be in awe of scale of history and the world we live in.
No two democracies are the same but what remains consistent across the democratic world is the presence of political parties. Their power and influence vary by country. Some parties live and die within months, while others continue to win elections and last for decades.
Which parties have been the most dominant? Which country has the highest voter turnout rate? Which countries have had the most parties hold the Head of Government? This project attempts to find the answers to some of those questions and others by measuring the success of 200+ political parties from over 70 countries across 1,000+ (and counting) elections.
Being a sports fan can be a painful experience, but some fan bases have it far worse than others. Are you one of them? You may think the teams you follow bring you misery, but what if you could know not only precisely how miserable they make you and how many more (if any) championship/cup/trophy wins you will likely see in the rest of your life? That's what this sets out to do, using the power of data!
An interactive breakdown of electricity generation sources by state using 2019 data from the U.S. Department of Energy. This was created using PlotlyDash and a touch of SCSS.
A python script for scraping historical team standings data from Sports-Reference.com for over 15 sports leagues from around the world.
Scrape a single Twitter handle or list of handles into a formatted .xlsx file. This also allows the user to check if any handles in a list are suspended, private, or incorrect.
Translates any word or phrase into one of several historical phonetic alphabets, including the one used today by NATO.
A simple script to scrape a list of keywords from Reddit into a neatly formatted .xlsx file. I needed this for my day job, but couldn't find one that went straight to a formatted excel workbook, so I made my own.
This script is for transcribing mp4 video files. It features a GUI using PyQT5. This repo is a slight spin off from vid2speech created by Dr. Alan Davies. You can find his tutorial for this here.
A mod/plugin for The Lord of the Rings Online that allows the player to check whether it time for one of the seven daily meals according hobbit tradition.
This blog was used as a reference. Also a great source for hobbit cooking recipes.
Want to support me? Feel free to buy me a coffee!
" TEXT " -