Data Visualization
2015 – 2016
A collection of data visualization projects for various clients.
Using the dashboard, users can explore selected oil and gas data, gain high-level insights, visualize trends, and create data alerts. The dashboard highlights trends in the industry and the performance of individual companies.


This was a mock prototype that incorporated the video platform’s key metrics and trends over time.

“I started by using Kimono to crawl the 500 most recent pages of the Pitchfork Reviews website for the name and artist of the 10000 most recent albums. I then modified an API I found to allow me to use Python to scrape the text, score and author the these 10000 reviews.
I used those data to train (in R) a machine learning algorithm called Elastic Net to learn what words were associated with more positive reviews, and which words were associated with more negative reviews. In general, the algorithm performed fairly well, but it couldn't have been perfect. First, each person has an idiosyncratic writing style, so there's going to be some error introduced by the way that different people use the same word differently. If that were the only problem, the errors would be randomly distributed across each reviewer.”
