Technical Articles

Clustering EPL Club Trajectories with k-means

tutorials

football

python

clustering

data-viz

premier-league

Technical walkthrough of clustering EPL club trajectories with k-means — feature engineering on position time series, scaling, k selection, and building a D3.js sparkline visualization.

Triple Double Russ

sports-analytics

python

In this post, we use webscraping to analyze Russell Westbrook’s (Russ) team performance when he records a triple double. We will use multiple Python modules and focus on Beau…

NBA Shot Charts - Part 1

sports-analytics

python

This post is the first in a series that demonstrate how to make shot charts by combining the Python module nba_api with the visualization modules matplotlib and seaborn.

Mortality Data and COVID-19 Disinformation - Part 4

tutorial

python

Comparing government mortality data with social media claims to evaluate COVID-19 disinformation.

Mortality Data and COVID-19 Disinformation - Part 3

tutorial

python

Creating U.S. mortality rate statistics by combining mortality and Census population data.

Mortality Data and COVID-19 Disinformation - Part 2

tutorial

python

Downloading U.S. Census population data to pair with mortality data for creating mortality rates.

Mortality Data and COVID-19 Disinformation - Part 1

tutorial

python

Gathering U.S. mortality data to investigate COVID-19 disinformation claims on social media.

NBA MVP Comparisons - Part 3

sports-analytics

python

In the last two blog posts we:
1. Gathered the relevant data for all NBA MVPs 2. Evaluated several machine learning models to select the MVP and chose the Latent…

NBA MVP Comparisons - Part 2

sports-analytics

python

Using machine learning regression models to identify controversial NBA MVP awards and who was robbed.

NBA MVP Comparisons - Part 1

sports-analytics

python

It’s Christmas and that means a full slate of NBA games. This time of year also provokes some great NBA discussions and the best NBA discussions are comparative. Arguments…

Milano Location History

how-to

The goal of this post is to visualize time spent in various Milanesi neighborhoods using Google location data and Python * This post utilizes code from Tyler Hartley’s visual…

Seattle Location History

how-to

The goal of this post is to visualize time spent in various Seattle neighborhoods using Google location data and Python * This post utilizes code from Tyler Hartley’s visuali…

Flights Analysis

how-to

The goal of this post is to visualize flights taken from Google location data using Python * We will create a .gif progressing through individual flights and a .png of all…

Positions Matter

sports-analytics

python

The Combine’s Positional Variability in Predicting Career NFL Performance

Social Media, Twitter API, and R

tutorial

python

A workshop on gathering, processing, and analyzing Twitter API data with R, created for the 2016 Population Association of America Annual Meeting.

---
title: "Technical Articles"
listing:
  contents: posts/technical
  sort: "date desc"
  type: default
  categories: true
  sort-ui: true
  filter-ui: true
  fields: [date, title, description, categories, reading-time]
page-layout: full
title-block-banner: false
---