The data newsletter by @puntofisso.
Hello, regular readers and welcome new ones :) This is Quantum of Sollazzo, the newsletter about all things data. I am Giuseppe Sollazzo, or @puntofisso. I've been sending this newsletter since 2012 to be a summary of all the articles with or about data that captured my attention over the previous week. The newsletter is and will always (well, for as long as I can keep going!) be free, but you're welcome to become a friend via the links below.
Every week I include a six-question interview with an inspiring data person. This week, I speak with Erin Davis, whose amazingly artistic data visualizations I've often linked to.
Speaking of Six Questions interviewees, after a long time of sending each other links, I had a virtual chat with Jeremy Singer-Vine, interviewee #2, that served to remind me why I really enjoyed going to events like Hacks/Hackers and getting acquainted with the data journalism world. It's because data journalists are the community where I found a quasi-total overlap with the 3 areas of data I love: a geeky curiosity in learning something through data; using storytelling as the main way to communicate your findings; and a willingness to break the boundaries of technology through multiple forms of media or approaches. I miss attending Hacks/Hackers in person, by the way.
'till next week,
Giuseppe @puntofisso
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"The Washington Post has compiled the first database of slaveholding members of Congress by examining thousands of pages of census records and historical documents".
"How the Covid-19 pandemic is shaping our shopping searches" – a data visualization that uses Google Trends to assess what trends have changed. Art direction by the legendary Alberto Cairo.
"Classes are always artificial", says Datawrapper's Lisa Charlotte Muth in this interesting article that shows how to produce a bivariate scatter plot and map to explore the relationship between GDP per capita and vaccination rates.
"How the legacy of former industrial sites pollutes American cities today". We've seen a similar article, based on the same EPA data, last week. This article on Grist takes a specific look at California.
Let's face it, unless you're Italian you won't be interested in the election of Italy's Head of State. However, the electoral system – which is based on supermajorities – is pretty famous for causing deadlocks and this simulator is quite good at exploring the chances of leading candidates.
Have you ever wondered how GPS works? This illustrated and interactive tutorial cracks it.
"All of the authors’ analysis was performed on logarithms of wage data", and The Economist newsletter explains how that works.
The very smart folks at Coefficient, a data consultancy, have publicly released their handbook on how they use Agile for data science/engineering/analytics projects.
My friend Riccardo Di Sipio, an esteemed physicist who worked at leading research centres, including CERN, who then "defected" to the world of industrial machine learning, has published a book that looks like a good intro to using ML in real life.
Here's an excerpt from the abstract: "However, there is no such thing as Machine Learning without a good deal of coding. Despite the large overlap in background knowledge of mathematics, statistics, software engineering and a generic ability in problem-solving, there is quite a bit of difference between more research- and product-oriented flavours of ML. While the former is mostly focused on creating new state-of-the-art models and new ways of training, the latter’s main concern is to make it work in real life. At times, trade-offs have to be found, with a specific constraint on keeping systems efficient both in terms of uptime and speed of execution. This can hardly be obtained by only using off-the-shelf solutions. The book also represents a unique resource to prepare a job interview for Machine Learning engineering positions."
"How HTR (Handwritten Text Recognition) and Related Technologies Are Empowering Family Discoveries". I was recently working on something similar related to handwritten notes, and I bet this might be useful to some data journalists.
Just because it's a nice (and scary) animation.
Bloomberg does an excellent job at showing we might be doomed unless we act.
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