Discover and read the best of Twitter Threads about #dataviz

Most recents (24)

THREAD: I used data to find #Spurs a capable backup to Harry #Kane
Constraints: Under 27 (enabling 3+ years of playing + potential re-selling), under £25m (Daniel Levy) & minimum of 900 minutes in his last season.

Two options:
1. A well-built strong forward to lead the line alone
2. An agile forward to press & play multiple roles as required.
Playstyle: I looked for strikers who brought a capable mix of pitching in with goals both when starting & off the bench and ability to feed others to score goals. This is important given Spurs' recent playstyle and reliance on wingers to score (Son, Lucas, Bergwijn).
Read 13 tweets
Every year Brazil faces a constant threat: dengue virus

After #Zika virus caused major outbreaks in 2016, cases of #dengue declined in 2017-2018, but then resurged in 2019. In this study we investigated the reasons for such fluctuations 📉📈


🔗… Dengue virus (DENV) is the most important and widespread mos
Something 'flattened' the dengue curve in 2017-2018. Every year in Brazil, cases of #dengue rise around March, when conditions are favourable (mosquitoes, rain, temperature). But, for some reason, in those two years, dengue cases were low in all regions of the country. 📉🦠
Infectious diseases are transmitted in a population of susceptible hosts following a rate called Force of Infection (FOI).

@RJOidtman, @guido_camargo and @TAlexPerkins estimated dengue FOI for each region in Brazil, and found viral transmission was indeed quite low in 2017-2018.
Read 11 tweets
A thread of mystifying and hilarious data visualisations from the "Australians" books, published in 1987 by the Australian Government. (ht @mikejbeggs) #ausecon #chartcrimes #dataviz
1. Spikes
2. BLUE STAIRCASE #ausecon #chartcrimes #dataviz
3. Wave, frozen wave of OJ. #ausecon #chartcrimes #dataviz
Read 13 tweets
#TidyTuesday Week 2020/32 ⚡ European Electricity by @EU_Eurostat inspired by @JohnMuyskens, @karim_douieb & @robradburn

Still experimenting with geofacets 🌐 And still experimenting with moon charts 🌘🌒🌖 Not enough green on that chart though.

#r4ds #rstats #ggplot2 #dataviz A geofacet of Europe that s...
Wasn't sure if I like the grey or white version better.
#FridaysForFuture #ClimateCrisis #ClimateAction #ClimateChange Image
Code for this and many other #dataviz'es on my GitHub:
Read 5 tweets
[#tekken #dataviz project] blog post 5, last one in the series. I feel dead after grinding on this project for about 3 weeks. Finally, it's done. Full post:… Process thread:
The final version finally has colour (yay!). These cards show one of Josie Rizal's move. It was important that these cards felt like it belonged to her. She is from the Philippines and her entire concept is inspired by her origins.
Even her colours are inspired from the Philippine flag.
Read 7 tweets
Construímos um novo aplicativo para acompanhamento das despesas do governo central. Agora sob a ótica do COFOG padrão internacional ONU.
É um dashboard com quatro abas para análises exploratórias. (1/n)
#RStats #DataViz #OpenData…
Na primeira aba, uma explicação geral sobre o dashboard. A contextualização do COFOG.
Os primeiros achados (2/n)
Na segunda aba, como as sub-funções de governo se juntam para formar as funções de governo.
Read 10 tweets
🎉 I have invented a new chart type. #dataviz

Would you like to see it? 👇
Black Lives Matter.
Now that I have your attention, I'd like to address the non-Black folks who are saying they wish they knew what to do right now.
I'll tell you what I have done, not that it is an exhaustive list (never will be) to give you inspiration and ideas.
Read 15 tweets
The debate about #SARSCov2 transmissibility in children and their viral load has intensified, in light of the new Israel high school superspreader event…
The UK data shows no Δ by age (2-11 yrs v adults)
The viral load in children being similar across age groups (a preprint) by @c_drosten and colleagues… engendered controversy, such as…
The Discussion of that preprint has been revised to address it
An unpublished report from Iceland showed child to adult and child to child transmission with genomic data, via @data_dinner
Read 9 tweets
Thanks to @crimmin @scurran_uw & @PopAssocAmerica for hosting an enlightening #Demography & #COVID19 webinar today. I wanted to follow-up with some links to people & resources, some of which I didn't have time to call out in the talk...
First @ikashnitsky & @jm_aburto used beautiful #dataviz to map age structure & #COVID19 risk regionally in Europe:
Read 22 tweets
Had fun live-streaming a chat yesterday with @IcahnMountSinai Director of Bioinformatics @AviMaayan

Before our @tidybiology code along, Avi dropped some words of wisdom 👇

On approaches to science:

Avi Mayan builds tools to enable biological discovery. He wants to figure out “how cells work”

He is gene-agnostic & disease-agnostic, meaning he can follow science wherever it takes him

This is a tremendous advantage for genuine & impactful discovery
On Data science:

#datascience infuses computation in biology, statistics, topology (networks), dynamic modeling

All providing a data driven approach

For his PhD, Avi tried reading 1000+ papers to understand cell signaling networks

“It was quite daunting, and it didn’t work"
Read 7 tweets
May 24, pandemic watch
The big 5 (BRIM-US)
Brazil's horrifying trajectory, within days of overtaking the US as leading daily toll of cases & deaths
Still no travel ban, watching this dramatic rise > 3 wks
Persistent ascent in cases and/or fatalities in Mexico, India and Russia
Linear and log-scale BRIM looks with the numbers…
Above for case, here for deaths
The separation of Brazil from RIM is quite striking
Read 4 tweets
We were busy #tracking #Covid19Kerala cases with, & DA team mems @ukp1513
@twik_dsc came up with #dataviz for #Covid19India situation. #CODDKeralam
Case/day vs. Cumulative Cases (log-log) for leading Indian states. @nikhilnarayanan @dumb_doh (1/8)
TPR for Indian states with more than 500 cases. #CODDKeralam #COVID19India @ukp1513 (2/8)
Total cases timeline (semi-log) for states with more than 500 cases. #CODDKeralam #COVID19India @ukp1513 (3/8)
Read 8 tweets
Here is the weekly update from COVID Forecast Hub, where we are storing forecasts of #COVID19 deaths in the US from 20 research groups. Our national ensemble combines 7 models and predicts that we will see ~113K deaths by June 6 (80% PI: 104K-123K).…

The ensemble model is now 85-90% certain that we will reach 100K #COVID19 reported deaths in the US by May 30.

This represents a slight increase and tightening in certainty compared with what the forecasts said last week.

We continue to see hints of increasing consensus among the models. Although the "best guess" predictions for total #COVID19 US deaths by early June range from ~103K to ~120K deaths. That difference represents a lot of people. More than sometimes die in a flu season.

Read 10 tweets
Dear #dataviz peeps, let's discuss: Is it ok to differentiate between categories with lightness, or should we use hues?

Different data viz book authors seem to have different opinions. 1/6
2/6 Dona Wong writes in her great book, "The Wall Street Journal Guide to Information Graphics", that shades of one colors are ok. Combinations like blue and orange are not.
3/6 While @visualisingdata writes on p257 in his fantastic Data Vis handbook, 2nd, that "you should not consider using variations in the lightness dimension" for differentiating categories – which means that we shouldn't even combine hues like yellow and orange.
Read 6 tweets
1. 🧵Hoy revisaremos conceptos básicos para facilitar la interpretación de diversas visualizaciones de datos (#DataViz) sobre la dinámica de la #pandemia de #SARSCoV2 en #México y #América. Gráficas log(casos|decesos acumulados ~ tiempo) son las más ampliamente reportadas 👇
2. 👆se muestra la relación log(casos) en función del tiempo, y 👇la de log(defunciones) ~ tiempo para los países con las 10 economías emergentes más grandes. La fase de expansión exponencial se visualiza como recta ascendente, llegando a una asíntota cuando no se acumulan más.
3. La visualización log-log de casos o decesos nuevos vs. acumulados refleja mejor aún la evolución/tendencia de la epidemia, en este caso separando países/regiones en celdillas. Las pendientes al final de la gráfica revelan las tendencias actuales, repuntes inclusive
Read 15 tweets
How will coronavirus impact #climatechange?

All your questions answered in this giant interactive data visualization project via @climate

A Pandemic That Cleared Skies and Halted Cities Isn’t Slowing Global Warming…
@climate The pandemic is a cataclysmic event so big and disruptive that it can be measured in the planetary metrics of #climatechange

#coronavirus #dataviz via @climate…
@climate To the impact is showing everywhere: seismic activity, power demand, street traffic.

@hellococomo has done an amazing job gathering video, photos, images and sounds
#coronavirus #climatechange…
Read 7 tweets
We’ve offered #DH undergrad and grad internships at Newbook Digital Texts since 2011 and have collaborated with around 200 @uw students during that time. #dayofdh2020 @nelcuw @ds_uw @SimpsonCenter @SvobodaDiaries @ebadiary @UWArtSci @uwcse @UW_iSchool
I collaborate with Prof. Walter Andrews and Dr. Mary Childs, amongst others. Our projects range from #Ottoman and #Georgian poetry to C19 travel journals from #Iraq and #Egypt.  
Our work is #opensource, and interns work on all aspects of the projects, including...
#Transcribing unpublished #primarysource material such as these diaries from C19 #Iraq @SvobodaDiaries @nelcuw
Read 9 tweets
I teach introductory no-prerequisite classes in #DH to undergrad and grad students. We focus on building sustainable, well-documented digital projects #dayofdh2020 @nelcuw @ds_uw @UW_iSchool #MLIS @SimpsonCenter
We use a variety of tools in class to explore humanities datasets and build exhibits including @omeka, @OpenRefine, @VoyantTools, #GaleDigitalScholarLab, @knightlab #StoryMapJS @neatline amongst others.
A few class highlights: Summer 2019’s online survey course through @UW_iSchool introducing students to concepts/methodologies of working with, and analyzing primary source texts using digital
Read 10 tweets
1/ Covid (@UCSF) Chronicles, Day 41

Still stable at @ucsfhospitals. Today, we have 12 patients, 4 on ventilators (Fig on L). Outcomes continue to be good: we’ve discharged 44 patients & had a total of 2 deaths. In SF: 1424 cases (up 16), 23 deaths overall (up 1)(Fig R).
2/ Despite stability @ucsf, SF hospitalizations stubbornly stable (Fig L), as are Bay Area cases (Fig R). Prob why leaders of 6 Bay counties today extended stay-home until 5/31 Tough call, but our leaders have called ‘em right so far, & earned our trust
3/ I’ll start with a few newsworthy items (#5-8), & then I’ll focus on impact of tech on Covid (& vice versa). Super-long (sorry), but lots to chew on and health tech is my favorite topic…
Read 25 tweets
1/ Covid (@UCSF) Chronicles, Day 36
After stats, a grab bag today – stuff that I’m reading, hearing & otherwise thinking about.

@UCSFhospitals stable, w/ 17 cases, 4 intubated. Last 1200 tests (PCR) @ucsf: 1% positive. Still only 1 death since start, 41 recovered & discharged.
2/ SF: 1233 cases, up 2(!). Hospitalizd pts flat. 21 deaths in SF, up 1 in last wk. Nice piece @TheAtlantic on SF’s success in Crushing the Curve Below, reaction when @LondonBreed banned crowds (early March), canceling @warriors hoops. Gutsy & life-saving.
3/ @tomaspueyo’s “Hammer & the Dance” is essential reading re: what comes next His new piece @Medium, “Learning How to Dance,” is Part 1 in brilliant primer on lessons from other nations re: controlling Covid in tricky next phase
Read 15 tweets
For April 21/22, you get to pick
Ascending @TheEconomist
Plateau @OurWorldInData
Long plateau @FT
No matter which log, semi-log plot, none look good for US fatality curves
To predict ~60,000 deaths for the US through August, the @WhiteHouse uses the most optimistic, @IHME_UW model.
If you look at the curves above and other models reviwed @UpshotNYT, you get the sense of the different scenarios…
The @FT April 22 update for the US #dataviz
The long plateau (~2,000 deaths/day) gets longer
That plateau is paralleled in the case curve, w/ little reduction
Soon to exceed 50,000 lost American lives, 1 million confirmed cases
Read 3 tweets
Hi #poptwitter! 🌍

Today, we’re excited to have @ikashnitsky for our first #PEExpertTwitterTakeover! He will be sharing info about his research all day, so make sure to follow along! Thank you, Ilya, for making this intro video and the floor is now all yours!
.@ikashnitsky: I’ve just finished my PhD thesis on unequal ageing in the regions of Europe, which I wrote at @NIDI_KNAW under the supervision of @BeerJoop and @leo_wissen. Soon to be defended at @FRW_RUG

All the papers & materials for the project are here
The outbreak of #COVID19 highlighted the importance of local differences in population age structures – aged populations are more vulnerable. With @jm_aburto we explored pandemic risks across unequally aged regions of Europe
Read 11 tweets
The rapid rise to #1
Better than my update of @PostGraphics fine work is their own, which appeared in the print edition, and has the weekly data (not cumulative that I used)
Read 3 tweets
1/ Covid (@UCSF) Chronicles, Day 31

Things remain stable here: @UCSFhospitals 17 Covid pts, 2 on vent; ZSFG has 27 pts, 10 on vents. SF overall, 1058 cases, up 39. Sadly, 20 deaths in city, up 3. Still a far cry from NYC's ~9000
2/ It’s been 1 mth since I launched Covid tweets. We were entering a phase I thought would be apocalyptic; I never dreamed I’d be chronicling SF’s remarkably good fortune. For nostalgia’s sake, here’s my 1st post (3/18) & 2nd (3/19)
3/ @ucsf, we were in crisis mode, scrambling to make scores of weighty decisions daily, from PPE policies to clinical workflow, steeling ourselves for a tsunami – one that, thankfully, never came. I fully expected we were heading into a hell like the one that actually hit NYC.
Read 15 tweets

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