An eclectic Spotify library, visualized with Chartify

I’ve been collecting songs in my Spotify library for a good few years now, so it’s fairly representative of my more recent tastes. After looking for tools to get detailed information on my library for analysis purposes, I ran across this Medium post by Dimitris Spathis on visualization of music tastes gathered from Sort Your Music.

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Tidy Beginnings (Tidy Tuesday week 26)

A few weeks ago, I undertook my first Tidy Tuesday prompt. If you’re not familiar, Tidy Tuesday is a weekly data project put together by the r4ds community on Twitter. Using the tidyverse in R, participants clean, restructure, and visualize data from a host of interesting sources.

Week 26, my first, looked at invasive species around the world and then more specifically in Africa. After an attempt at creating a cartogram for this dataset which absolutely failed to launch due to software issues (and which I will write about at a future date to save everyone else the headache), I settled with a choropleth map and dumbbell plot to focus in on invasive plant species.

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Analyzing Pittsburgh dog data in R

As part of my work during 2018’s Summer of Data Science, I decided to undertake a data project in R on top of my studies with textbooks and DataCamp.

Now, anyone who knows me can attest to how much I want a dog in my life. I figured, until I can make that happen, I could at least look at the dog trends in my new home of Pittsburgh, Pennsylvania. Fortunately, the Western Pennsylvania Regional Data Center has plenty of locally-focused datasets, including multiple years’ worth of dog license information.

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Creating a soccer team for FIFA 2018 with machine learning

Recently I began working with Kaggle’s datasets and kernel environment for data science, and have found them incredibly useful for quick, self-contained projects and trying out new techniques with Python. Kernels even have version control!

In an effort to branch out of my usual subjects of environment and animal-focused data, I gave myself a challenge: Sports. In this case, specifically soccer. Now, I have no background in soccer, or watching it, or knowing much of anything about it, but I set out to find what was most important in creating a team, and how to communicate player selection evaluation to others creating a team.

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