436: quantum of sollazzo
#436: quantum of sollazzo – 24 August 2021
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.
I’ve been very busy and travelling this week, so it’s a slightly less dense issue of Quantum than usual.
Every week I include a six-questions interview with an inspiring data person. This week, I speak with Clara Guibourg of Newsworthy, whose interactive climate data investigations and applications you might have seen featured in Quantum of Sollazzo over the years.
If you’re looking for a #ddj job, the BBC are hiring a data journalist for South Asia Visual Journalism team.
‘till next week,
Giuseppe @puntofisso
Six questions to...
Clara Guibourg
Clara is a data journalist at Newsworthy.
What is your daily data work like and what tools do you use?
I work with “automating” local data journalism, finding the right angle on a story for each Swedish municipality, say. My typical workflow starting a new project is: research, find data, clean, clean, clean again, analyse and visualise. This part is all heavily R-based. The next part is writing hundreds of local articles. Thankfully, I don’t have to do this by hand, but instead use the homemade “robot writer” my clever colleagues Jens and Leo have developed. This is a Node.js-based interface which generates text from data and makes it possible to write dynamic articles with programmatic logic.
Tell me about a data project that you're proud of...
How much worse are heat waves going to get in your municipality? I was pleased with the way this combined modelled temperature data and population projections to show a granular picture of the parts of Sweden that can expect to face greatest health risks from heat waves in future, with a combination of many hot days and a large elderly population.
...and a data project that someone else did and you're jealous of.
So many! I’m especially interested in climate data, but it can often feel quite abstract. So I’m always looking for good examples where the topic is covered in a tangible and engaging way. Recently I enjoyed NYT’s article on tree cover inequality, a really smart analysis of neighbourhoods’ median income and canopy cover (or lack thereof). ProPublica’s maps showing the effects on a “transformed United States” were also really good, not least the way they combine specific effects on things like sea level and crop yields into a total climate risk index county by county.
If I say "dataset", you think of...
Excel. I barely work with it these days, but somehow this is still how “data” looks to me.
Give someone new to data a tip or lesson you wish you'd learned earlier.
There’s always something wrong with the data. Take the time to explore the data and find out what it is early on, it’s much less stressful to tackle then than when you discover the problem right before hitting the publish button.
Data is or data are...
Data is. No question!
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Topical
In many cities, it is becoming too hot to work
Patrick Scott, writing for CityMonitor, shows that “the number of high heat days is increasing rapidly across the world, and the implications for businesses are profound.“
Productivity seems to be badly affected by climate change, especially in terms of excess heat (unsurprisingly for me, having worked for a couple of summers in Bologna, with 38C and 90% humidity).
Days with extreme heat are likely becoming more frequent
As a way to compound what we’ve learned in the article above, here’s Datawrapper’s Gregor Aisch taking a look at a way “to make warming degrees a little less abstract and a little more scary.”
How the racial makeup of where you live has changed since 1990
“A Washington Post analysis of newly released tract-level census data reveals the shifting racial composition of neighborhoods nationwide“
The analysis also calculates a “Diversity Index” for any given area.
See How Vaccines Can Make the Difference in Delta Variant’s Impact
“Here’s how a Delta-driven outbreak might unfold in two hypothetical groups of people, all of whom are exposed to enough of the virus to infect a person”.
Interactive explainer by The New York Times.
Tools & Tutorials
Automatically enclose points in a polygon
Just a useful R function.
SQLite via AWS
This is a python library to query a sqlite database stored on AWS s3 (without downloading all of its data). Read-only.
How to design an enclosure using photogrammetry? – The Complete Guide
Although this guide is for the specific use case of creating an enclosure, it gives a very good step-by-step introduction to creating a 3D model via photogrammetry (i.e. creating a point cloud via photographs).
Census Reporter
Census Reporter is a free, open-source project, that helps exploring US Census data.
Strava animated routes
Take your Strava activities (or any GPX route) and create a video displaying them. Not all my doing, but I improved the original code by Marcin Wichary to be easier to re-apply, and added a more in-depth set of instructions. The picture below is what it looks like at the end, but this tweet shows the animation at work.
How to map Rio de Janeiro’s six million residents
Brilliant write-up by Marie Segger and colleagues on the Economist’s Off The Charts newsletter.
“A few weeks ago Sarah Maslin, our Brazil correspondent, asked our team if a dot-density map that she had come across in her research could accompany her piece about racial segregation in Rio de Janeiro. The map showed each of the city’s 6m residents as a single dot, with different colours denoting their skin colour. Unfortunately, we could not get hold of the underlying data for the map—so we had to recreate the numbers ourselves. In theory, it was a straightforward task: we had to combine the demographic data from the Brazilian census with the geographical information of each census tract within Rio de Janeiro. This would tell us how many people are located within each area, alongside their racial identification: branco (white), pardo (mixed) or preto (black). As anyone who has ever dabbled in any kind of programming knows, nearly every problem has been solved before. “
quantum of sollazzo is 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.
