I look at the relationship between risk and expected return in a number of datasets.
I demonstrate a technique for easily using version control along with Jupyter Notebooks.
I come up with a new twist on this probability theory problem and propose a solution.
I show a way to draw numbers from arbitrary joint probability distributions.
A model and d3.js visualization to communicate my thoughts about how the world works.
An interactive, draggable visualization showing turnout, party margins and more.
I compare the turnout for the Women's March and Tea Party by city and state.
I look at potentially close seats in the House and Senate for 2018.
I build an interactive bubble chart to show trends in the 2000-2016 election results by county.
I look at a few graphics showing the election results and build a few of my own.
I take a look at the relationship between social services spending, health spending and DALY burdens across the OECD.
I re-create the polar climate change visualization that went viral using d3.js.
I show a technique for making a stacked chart using the Pandas pivot function
I look at the potential impact of including pandemic disease and a longer life expectancy into the GBD estimates.
Looking at the relationship between individual characteristics and the responses for the economics expert panel
I explore the data from the economics expert panel, focusing on the confidence and consensus among the responses.
I scrape a dataset of all the IGM Panel responses from their website using Python
Using the python library Pillow to build a dataset by counting the pixels of an image
An application for checking Gmail via SMS message, built with Python and Twilio
A few tips on some difficult D3.js concepts
Weighing the costs and benefits of blogging
A few ground rules for the blog before getting started