I recently moved back to Philadelphia after finishing my astrophysics PhD at Berkeley. To get reacquainted with my hometown, I began exploring the treasure trove of data that is OpenDataPhilly. With over 300 public datasets, there's a lot to dig in to. I started with the parking violation data, which ranges from 2012 to 2016. The data offered a good chance to learn some of the latest data viz tools. Namely, I took advantage of the open source javascript library dc.js, which neatly ties together the d3.js and crossfilter tools. Here, I'll discuss these tools as well as some of the trends that jumped out of the ticketing data.

The data visualization is up and running at http://nickhand.pythonanywhere.com, and the source code is hosted on my GitHub. Keep reading for the gritty details, or otherwise, happy exploring!

This past year I got married, and it was a blast. After months and months of planning, we lucked out and nothing major went wrong on the day of (despite some last minute rain forecasts for our outdoor venue). During the planning process, we ran into all of the usual challenges. To make matters worse, I was living in CA at the time while my fiancée was in NJ, and we were both busy with school (astrophysics Ph.D. for me, M.D. for her). Unsurprisingly, we looked for every opportunity to make the planning easier. As one example, I made an automated, online RSVP system for our wedding website. After some initial set-up, we were able to sit back and watch our master guest list (stored on our Google Drive) track the RSVP responses of our guests. And better yet, the whole thing was free.

There are a lot of options out there for online RSVP forms, but nearly all of them charge some sort of fee. So, I ended up combining a bunch of free services, and using some Python to glue them together, to build our RSVP system. In this post, I'm going to outline the main steps involved in the hope that it might make wedding planning just a bit easier for some future couple.

Hello, and welcome to Offhand Remarks! I'm Nick Hand. Let me start off by apologizing for the terrible pun in the title of this blog. I'm a recent astrophysics Ph.D. grad from Berkeley who is currently living in Philadelphia looking for data science jobs. My Ph.D. focused on improving the tools that astronomers use to analyze data sets that map the three-dimensional Universe on its largest scales (this video is a great visualization of one of these data sets). My studies offered me a chance to use Python and open-source software every day and helped teach me the power of data and statistics for offering insights into complex questions. As a cosmology Ph.D., I was essentially a data scientist tasked with extracting insight from the Universe itself. I am the lead developer of one open-source, cosmology Python toolkit and have contributed to several other open-source Python projects.