428: quantum of sollazzo
#428: quantum of sollazzo – 29 June 2021
The data newsletter by @puntofisso.
What a week, folks. I had my second jab on Thursday and felt a bit broken, but overall really happy to see the light at the end of the tunnel (which was, obviously, a side effect?). I managed to put in a few hours of work at the allotment each evening, so to get ahead of potential vaccine-induced weakness.
In more interesting news, look below for a true star of data journalism: Marie Segger, data journalist at The Economist and lead author of their “Off the Charts” newsletter, answers this week’s Six Questions.
This deserves a special mention: Owen Boswarva’s UK Addresses Primer has been updated. It’s one of the most comprehensive yet digestible articles you’ll read on the topic of open data about postal addresses (well, about the lack thereof, in reality).
I’ve otherwise been spending my evenings generating maps for my Etsy print shop, which is now mostly made of high-quality, fine-art giclée prints on heavy paper. There is a general 10% discount for newsletter readers on this link.
However, if you recommend me a city location (using this bounding box locator) and I pick it up for the shop, you’ll get 20% off your first order.
‘till next week,
Giuseppe @puntofisso
Six questions to... Marie Segger
Marie Segger is a Data journalist at The Economist .
What is your daily data work like and what tools do you use?
My work looks very different each day, I research, write, edit and I also lead interviews for data-driven articles for The Economist. For data work I rely on Google sheets and Rstudio and I'm still trying to get more consistent with my usage of GitHub.
Tell me about a data project that you're proud of...
I'm very proud of our data newsletter. We launched "Off the Charts" at the beginning of the year and lift the curtain on the inner workings of The Economist's data team each week. We've written about the data-vis tools we use, how we source covid-19 data and why we rarely use polar charts, to name just a few examples. It's not really my work though—I'm just the editor and feel very lucky to work with such a brilliant team that has interesting things to say about the behind-the-scenes of their work every week. I also really hope that it helps make our data journalism more accessible.
...and a data project that someone else did and you're jealous of.
I really like the New York Times's "What's going on in this graph?" series. It's a project aimed at teachers to help them educate students on all things data. I think data literacy is so important and it's great to see news outlets committed to increasing it—hopefully it means that we won't have to have discussions about whether readers understand scatter plots anymore in the future. I also loved the FT's "Chart doctor" column.
If I say "dataset", you think of...
Cleaning.
Give someone new to data a tip or lesson you wish you'd learned earlier.
Everyone else is learning by doing, too, so there is no need to feel insecure about things you don't know about (yet)! Ask all those questions you have and keep looking for opportunities (new projects!) to learn more.
Data is or data are...
The Economist style guide says "data are", so I'll have to go with that.
Topical
Climate coverage booms, but still pales compared to weather
“Climate-focused news initiatives are pushing media outlets to devote more coverage to the way climate change impacts extreme weather events.“
Interesting snapshot from Axios, which uses the Stanford Cable TV News Analyzer linked below.
What tree rings reveal about America’s megadrought
Tree rings record climate variability. Extraordinary, and extraordinarily visualized by Alvin Chang at The Guardian.
Republicans Fall Short in Voting-Rights Crackdown While Adding Hassle at Polls
“Republicans say that the changes are needed to restore confidence in elections after President Donald Trump’s false claims that massive fraud cost him a second term. Democrats argue the laws are aimed at suppressing votes from Black and Latino citizens after record-setting turnout, going so far as to label the moves “a new Jim Crow.”“
A brilliant data-driven investigation by Bloomberg Graphics.
How America’s top hospitals hound patients with predatory billing
An analysis by Axios sheds light on something that is very US-specific from our free NHS perspective. Nonetheless, it’s very interesting and it comes with a tool to search through data for the 100 largest hospitals.
Tools & Tutorials
Stanford Cable TV News Analyzer
“Use this tool to count the screen time of who and what is in cableTV news.“
Are men talking too much?
A simple tool to measure the relative share of dialogue.
Data protection in journalism (EU): a practical handbook
Edited by Federico Caruso of the European Data Journalism Network, this helpful handbook is “a practical guide to help journalists deal with the processing of personal data within the European context”.
A Concrete Introduction to Probability (using Python)
This is a brilliant Jupyter notebook that will guide you through concepts of Probability using Python. It covers all the classics, from the basic understanding of outcome calculation to complex urn problems and simulations.
ArchieML
ArchieML is a “ArchieML is a structured text format optimized for human writability, developed by journocoders at The New York Times in order to enable the fast rendering of structured news. Pretty brilliant. They’ve used it, for example, for this visual article. It has a number of parsers in all major programming languages, and a useful sandbox.
(via The Economist’s Off The Charts newsletter)
Data thinking
What I’ve learned about data recently
Laurie Voss has written this interesting blog post to which I strongly relate, especially the data scientist vs engineers debate (I always encourage data folks to be a bit of both, but being a scientist has a stronger appeal to many, who are then disappointed by the actual content of their role).
(via Guy Lipman)
Why you sometimes need to break the rules in data viz
“Best practices help us to avoid common pitfalls in data visualisation — but we shouldn’t follow them blindly”.
Ok, so many links this week are from The Economist, but I can’t help when they publish so much great content. This is a very insightful blog post by Visual Data Journalist Rosamund Pearce.
Dataviz & Interactive
DivineComedy.Digital
A highly visual (maybe… a bit too visual?) exploration of Dante’s poem.
(via the immensely good – and immense – WebCurios)
A full month more above 20°C
Lisa Charlotte Rost of Datawrapper shows how Berlin has experienced, over the past few decades, increasingly longer spells of (unbearably) hot temperature.
“Is this normal?“
AI
Objective or biased
This interesting analysis of AI for video-driven recruitment was featured in issue 410, but it has been useful to me recently (as my team is working on a project looking at how we could control bias in AI-driven recruitment). So here it is again.
Become a GitHub Sponsor. It costs about the price of a coffee per month, and you’ll get an Open Data Rottweiler sticker (and other stuff). Or you can Buy Me A Coffee.
quantum of sollazzo is also supported by ProofRed’s excellent proofreading service. If you need high-quality copy editing or proofreading, head to http://proofred.co.uk. Oh, they also make really good explainer videos.
