Thanks for stopping by! 👋🏽 I am motivated by data visualization and using data as a tool to make operations more efficient. I prefer to use Python and JavaScript with Sheets for analysis but I also have experience with R. For visualizations I use Tableau or Looker.
I've worked with top companies like Uber and Coinbase working on projects using data to systematize operations, and analyze their datasets. I'm always looking to strengthen my knowledge, as such I have completed the Google Data Science , and the Data Analytics General Assembly courses where I explored the core aspects of data science.
A brief analysis into the Boxing Champions of the four major boxing sanctioning bodies (WBA,WBC,WBO, and the IBF) also known as the 'Alphabet Soup'. Using BigQuery and a Jupyter notebook I process over 500,000+ rows of boxing data from 1962-2020, it is then visualized with Tableau.
A project to analyze how Netflix user ratings relate to box office results. This repo contains a Jupyter Notebook that processes, analyzes, and visualizes streaming metadeta dataset containing 100,000 user records.
Although I prefer to use python for data pre-processing, I enjoy building simple apps in google sheets for tasks like these.
Here is a simple multi-functional data cleaning app that can color code duplicate entries, remove blank rows, and more using Google Sheets and JavaScript.