Cars are getting smarter and more connected, yet how much have you explored the technology that helps run our vehicles? I was curious to see how I could connect to my vehicle’s communication center and what kind of interface I could create in Wolfram Notebooks to report on the data gathered.
Data Analysis and Visualization
Wikidata is a large, community-curated repository of freely usable data. Version 12.1 of the Wolfram Language introduced dedicated functionality to access Wikidata. We came up with a new kind of entity: a fundamental building block called ExternalIdentifier, which I’ll explain in more detail shortly.
In his blog post announcing the launch of Mathematica Version 12.1, Stephen Wolfram mentioned the extensive updates to Dataset that we undertook to make it easier to explore, understand and present your data. Here is how the updated Dataset works and how you can use it to gain deeper insight into your data.
In June 2019, Stephen Wolfram announced the Wolfram Function Repository, a curated repository of functions that can be employed immediately in the Wolfram Language. Since then, the Repository has grown to include more than 1,000 functions in over 20 categories.
Functions included in the Repository range from those that are more general and utilitarian in nature to others with very specific applications. As with all Wolfram Language functions, Repository documentation pages contain examples showing how to use the functions. We’re featuring a few of the functions submitted to the Repository so far that showcase the variety of functions our users have built.
When 20 presidential candidates duke it out on the debate stage, who wins? Americans have been watching a crowded and contentious primary season for the 2020 Democratic nomination for president. After the debates, everyone’s talking about who got the most talk time or attention, which exchanges were most exciting or some other measure of who “won” the night—and who might ultimately clinch a victory at the caucuses. So I decided I’d do a little exploration of the debates using the entity framework, text analytics and graph capabilities of the Wolfram Language and see if I could come up with my own measure of a “win” for a debate, based on which candidate was most central to the conversation.
Who has not encountered a stink bug? Perhaps the better question is not if, but when. I remember well my first interactions with stink bugs—partly because of their pungent, cilantro-like odor, but also because in my native Catalan language they are called Bernat pudent ("stinky Bernat") and Bernat is my twin brother's name.
So when I encountered the stink bug again when visiting Champaign, Illinois, for the 2019 Wolfram Technology Conference, it brought up a lot of fond childhood memories. This time, however, two things had changed: the frequency of encounters with the stink bug seemed exponentially greater, and I now had the Wolfram Language to more fully (and computationally) satisfy my curiosity about this reviled insect and its growing impact on our ecosystem. So to get a better picture of the arrival and spread of this invasive bug across the US, I used available observation data and the Wolfram Language to make a map of sightings over the past two decades.
We’ve gathered some of our favorite Wolfram Community posts showing the variety of applications made possible with the Wolfram Language.
Looking to fulfill your New Year's resolution of learning new data science skills? Join Wolfram U for Wolfram Technology in Action: Data Science, a three-part web series demonstrating a range of data science applications in the Wolfram Language. These 90-minute sessions feature recorded talks from the 2019 Wolfram Technology Conference, along with live presentations by Wolfram staff scientists, application developers, software engineers and Wolfram Language users who apply the technology every day to their business operations and research.
Newcomers to Wolfram technology are welcome, as are longtime users wanting to see the latest functionality in the language.