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The Washington Post, in an effort that I’m sure took more energy and time than it looks, compared U.S. abortion laws against those in other countries:
In the last three decades, countries around the world have made it easier to legally get an abortion. In some parts of the United States, however, it’s gotten harder. Just this month, Mexico’s supreme court ruled to decriminalize the practice. Argentina’s Senate legalized abortion in December. Meanwhile, New Zealand, Thailand and Ireland have all taken steps to ease abortion restrictions in recent years.
Hm.
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Zan Armstrong, Ian Johnson, and Mike Freeman for Observable wrote a guide on analyzing time series data. Using an energy dataset, they show how asking different questions can lead to different findings and visualizations:
These are stories about analyzing data that changes over time. While most of us don’t dig into data about energy day-to-day, we hope the feel of this data and these questions will be familiar to anyone who regularly faces questions like “what changed?”, “what happened?”, “was that normal?”, “what is typical?”, and “did things go as expected?” We hope that this will spark an idea about how to look at your own data in a new way.
I will never tire of the multiple-views-from-the-same-dataset teaching device.
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Inspired by a graphic on Reddit, Jim Vallandingham expanded the format for all the shows. Search for a show and get a heatmap for average ratings by season and episode. See how your favorite show went into the dumpster at the end or withstood the test of time. Nice.
The data comes from IMDb Datasets, which seems like a fun time series dataset to poke at.
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Cloudflare describes how things looked from their point of view the day that Facebook, along with its other properties, went down. From the Border Gateway Protocol, which defines routing information:
A BGP UPDATE message informs a router of any changes you’ve made to a prefix advertisement or entirely withdraws the prefix. We can clearly see this in the number of updates we received from Facebook when checking our time-series BGP database. Normally this chart is fairly quiet: Facebook doesn’t make a lot of changes to its network minute to minute.
But at around 15:40 UTC we saw a peak of routing changes from Facebook. That’s when the trouble began.
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Aaron Steckelberg and Tik Root for The Washington Post provide a visual guide on how to protect your home from wildfire. It starts with an ember floating carefree in the air, and then the tour highlights actions you can take.
Can’t wait for the guides on how to protect your home from flooding and/or how to dress for extreme temperatures.
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Companies collect and aggregate location data from millions of people’s phones. Then that data gets sold in a multibillion-dollar market. Jon Keegan and Alfred Ng for The Markup report on who’s doing the collecting and where your data goes:
Once a person’s location data has been collected from an app and it has entered the location data marketplace, it can be sold over and over again, from the data providers to an aggregator that resells data from multiple sources. It could end up in the hands of a “location intelligence” firm that uses the raw data to analyze foot traffic for retail shopping areas and the demographics associated with its visitors. Or with a hedge fund that wants insights on how many people are going to a certain store.
“There are the data aggregators that collect the data from multiple applications and sell in bulk. And then there are analytics companies which buy data either from aggregators or from applications and perform the analytics,” said Tsiounis of Advan Research. “And everybody sells to everybody else.”
It just makes you feel all warm and fuzzy inside.
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Members Only
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Whether it’s because of experience, physical ability, or education level, some jobs tend towards a certain age of worker more than others.
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UnstableGround is a project from the Woodwell Climate Research Center that focuses on climate change in the Arctic:
Climate change is transforming the Arctic, impacting people and ecosystems across this vast region. But because our climate system is connected globally, what happens in the Arctic doesn’t stay in the Arctic.
Discover how Arctic landscapes are changing and learn about the consequences for communities across the globe.
A stories section uses maps, charts, and photographs to communicate the ongoing research.
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Before you get into analysis and visualizing data with R, you need to know the basics. Steve Haroz wrote a guide on getting started:
This book is a short introduction to the R language. It covers the basics of R that are not covered by analysis and visualization guides like R for Data Science. Consider it a quick way to get up to speed on R before diving into the analysis and visualization aspects.
This example-focused guide assumes you are familiar with programming concepts but want to learn the R language. It offers more examples than an “R cheat sheet” without the verbosity of a language spec or an introduction to programming.
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Researchers evaluated 158 Covid-19 dashboards, assessing design, implementation, and usefulness. Marie Patino for Bloomberg CityLab reports:
“All of these dashboards were launched very early in the pandemic,” said Damir Ivankovic, a PhD student at the University of Amsterdam. “Some of them were developed literally overnight, or over three sleepless nights in certain countries.” With Ph.D. researcher Erica Barbazza, Ivankovic has been leading a set of studies about Covid-19 dashboards with a network of researchers. For an upcoming paper that’s still unpublished, the pair have talked to more than 30 government dashboard teams across Europe and Asia to better understand their dynamics and the political decisions at stake in their creation.
In 2020, suddenly governments at all levels required an online dashboard that showed data at least near real-time, but there were constraints with software, design, and data sources, along with people to implement. So groups worked with what they had.
On the other end, everyone checking these dashboards on the daily were getting their own lessons in interpreting trends, missing data, and variation.
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Poyang Lake is China’s largest freshwater lake, but sand mining has changed its depth and structure, which messes up the ecosystem. Simon Scarr and Manas Sharma for Reuters used satellite imagery to show the scale and disruption of the mining activities.
The ships look like little bugs slowly eating away at the coastline.
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For when you want to fill SVG polygons with patterns instead of or in combination with color, Thomas Michael Semmler has a copy-and-paste collection. It’s just the basics, but it’s a convenient reference that could provide a starting point at the least.
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Derek Thompson for The Atlantic highlights recent research comparing mortality in America against rates in Europe:
According to a new working paper released by the National Bureau of Economic Research, Americans now die earlier than their European counterparts, no matter what age you’re looking at. Compared with Europeans, American babies are more likely to die before they turn 5, American teens are more likely to die before they turn 20, and American adults are more likely to die before they turn 65. At every age, living in the United States carries a higher risk of mortality. This is America’s unsung death penalty, and it adds up. Average life expectancy surged above 80 years old in just about every Western European country in the 2010s, including Portugal, Spain, France, Italy, Germany, the U.K., Denmark, and Switzerland. In the U.S., by contrast, the average life span has never exceeded 79—and now it’s just taken a historic tumble.
Find the full NBER paper here.
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How to Make Print-ready Graphics in R, with ggplot2
You don’t have to use illustration software to polish your graphics. If keeping everything in R is your thing, this tutorial is for you.
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In fall 2020, Suzanne Brennan Firstenberg planted a flag for each American who died from Covid-19. There were over a quarter of a million flags at the time. The art installation is back at the National Mall, but this time there are over 660,000 flags. The scale is just…a lot.
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For the employed, unemployed, and those not in the labor force, these charts — using an oldie but goodie visualization layout — show the percentage of people doing an activity over a day in 2020.