Treemap tour of political donations

The Digital Story Innovation Team for ABC News in Australia looked at political donations from the gambling industry. The piece goes all-in with treemaps in a scrollytelling format to show categories and individual donations.

It starts with an individual point and keeps zooming out more and more. Then when you think it’s done, it zooms out more.

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Simulating how just a little gender bias in the workplace can lead to big effects up the chain

Yuhao Du, Jessica Nordell, and Kenneth Joseph used simulations to study the effects of small gender biases at entry level up to executive level. It doesn’t take much to skew the distribution. For NYT Opinion, Yaryna Serkez shows the simulation in action with moving bubbles and stacked area charts for each work level.

The simulation imagines a company where female performance is undervalued by 3 percent. Each dot represents an employee, and they either move up with promotions or stay still. The distribution of men and women start even but end very uneven.

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Possible cheating seen in a scatterplot

When plotting Russian election results, a structured grid patterns appear. From The Economist:

When Dmitry Kobak and Sergey Shpilkin, two researchers, analysed the results, they found that an unusually high number of turnout and vote-share results were multiples of five (eg, 50%, 55%, 60%), a tell-tale sign of manipulation. According to Messrs Kobak and Shpilkin, there were at least 1,310 polling stations (out of 96,325) with results that were suspiciously tidy, with rounder numbers than you would expect to see by chance.

I’m not familiar with Russian elections, but this seems like lazy cheating. Are they just making up numbers by hand or what?

Check out the full results of Kobak and Shpilkin’s analysis in Python notebook form.

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Visualizing time-based data

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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Heatmap of average IMDb ratings for all the shows

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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How Facebook disappeared from the internet

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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Assessment of the Covid-19 dashboards

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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Using rates for more relatable Covid-19 numbers

With millions of Covid-19 deaths worldwide, and hundreds of thousands in the US, the absolute counts have been a challenge to relate to for a while. The Washington Post leaned into rates to communicate scale at the individual level. 1 in 500 Americans died from Covid-19 so far.

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Data visualization activities for kids

Nightingale has a kid’s section with printable visualization activities. Get the kids started early while they absorb information like a sponge.

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Cases, hospitalizations, and deaths for vaccinated vs. unvaccinated

The CDC released a chart that shows case, hospitalization, and death rates for fully vaccinated (blue) against not fully vaccinated (black). As you might expect, the rates for the fully vaccinated are much lower, especially for hospitalizations and deaths.

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