Here's one purely for fun - a wordcloud built from the Supreme Court's opinion on Arizona et al. v United States. Word clouds, though certainly not the most scientific of visualization techniques, are often engaging and "fun" ways to lead into discussion on NLP or topic modeling. Arizona et al. v United States wordcloud
Based on Launchpad traffic and mailing list responses, Gabor and Tamas will soon be releasing igraph 0.6. In celebration, I’ll be publishing a number of helpful lists and tables I’ve put together to organize information about igraph. In this post, we’ll cover the community detection algorithms (~i.e., clustering, partitioning, segmenting) available in 0.6
I first heard about Python pandas from a friend at RenTech or AQR in the early summer of last year. At the time, the project was little more than a documentation page and a few wrapper methods around numpy. Since then, pandas has matured into a very useful and featureful addition to numpy, scipy,
The NATO summit is currently being held in Chicago, and, as is typical for NATO or G# summits, the streets and tweets are full of dissent. In the spirit of my past investigations of online dissent (#jan25, #25bahman, #12fev, #wiunion, #cn220, #march15), I thought I would investigate the #nonato tag, where Twitter users around
Let's say you've used my Python script to automate the download of a hashtag or search phrase from Twitter (in a Unicode safe way, unlike within R). Now let's say you want to visualize the number of tweets over time. Easy enough - I've also shared this R/ggplot2 code that accomplishes the task. However, let's say
In my last post on CloudSearch and eDiscovery, I described something like “Google” for eDiscovery emails. FedEx or DropBox your data to an eDiscovery service provider like myself, and rest assured that you’ll soon have a powerful, web-based user interface for searching and visualizing your digital discovery materials. As a technical follow-up to
In the last post on AWS CloudSearch, I provided a tutorial on the creation of a simple CloudSearch domain for Supreme Court decisions. This walkthrough described the steps of creating a domain, configuring access policies and indexing, populating the index, and using the search API. We were left with a functioning case search database.
It should be pretty clear by now that two things I'm very interested in are cloud computing and legal informatics. What better way to show it than to put together a simple AWS CloudSearch tutorial using Supreme Court decisions as the context? The steps below should take you through creating a fully functional search
Here's a fun example of how you might use my data on Congressional bill length and complexity. Imagine you want to understand the empirical distribution of Flesch-Kincaid reading level for Congressional bills and how this distribution is related to bill stage. A first step might be to visualize this relationship. Based on this
When I put together my original post on the length and complexity of Congressional bills, I was hoping to build forward momentum on the project. The goal was to build a simple, sortable and searchable interface to explore and visualize the data. As usual, however, paying employers and consulting clients got in the way
