Layering Maps and Data At Algorex Health, we make a lot of maps and get a lot of questions about the tools we use to make them. So, I thought I would briefly describe our process and the tools we use. I covered the basics of geographic charting in a past blog post and some of that terminology will be repeated here. We use to two primary data visualization systems at Algorex Health both of which were chosen for their support withthin the Python/Jupyter stack, ease of use, and/or aesthetic flexibility:
Continue reading

Flying to Orlando

When is Data Big? This week the health world turns to Orlando for the annual conference of the Health Information Management Systems Society annual conference. it is absolutely one of the biggest events in health IT and one of the top 25 trade shows in the entire country. How many people attend HIMSS each year? We could search one of hundreds of press releases about the event from exhibitors. We could even visit the link above from Trade Show news.
Continue reading

Everything You Never Wanted to Know about Geographic Charting Before the start of seventh grade, my family moved, and I started a new school that had as required module, cartography. Over a few weeks, we painstakingly drew maps of states, continents and eventually the entire world. My backpack became filled with various stencils, a compass, colored pencils, pens of multiple weights, and even tracing paper. It was one of the more frustrating parts of my schooling and I remember thinking “Why would I ever need this?
Continue reading

Almost 10 PieCharts 10 Python Libraries Here is a follow-up to our “10 Heatmaps 10 Libraries” post. For those of you who don’t remember, the goal is to create the same chart in 10 different python visualization libraries and compare the effort involved. All of the Jupyter notebooks to create these charts are stored in a public github repo Python-Viz-Compared. Each Jupyter notebook will contain one chart (bar, scatter etc) and then up to 10 different ways of implementing them.
Continue reading

10 Heatmaps 10 Libraries I recently watched Jake VanderPlas’ amazing PyCon2017 talk on the landscape of Python Data Visualization. That presentation inspired this post. In programming, we often see the same ‘Hello World’ or Fibonacci style program implemented in multiple programming languages as a comparison. In Jake’s presentation, he shows the same scatter plot in several of the libraries he featured. Below, I am following the same formula. I am recreating a heatmap about airline flights, in ten different python visualization libraries.
Continue reading

Author's picture

Algorex Health Technologies

A blog for technology, policy, and grievances in the Open Health World

Opening the Healthcare Technology Doors

Boston, Massachusetts