Talk about a massive global footprint, #Netflix! #datavizhttps://t.co/saDH9dDRZr pic.twitter.com/8502kwUlQI
— Randy Olson (@randal_olson) October 19, 2018
Talk about a massive global footprint, #Netflix! #datavizhttps://t.co/saDH9dDRZr pic.twitter.com/8502kwUlQI
— Randy Olson (@randal_olson) October 19, 2018
🏀🤓🔥, #NBA's back! Time to revisit…
— Mara Averick (@dataandme) October 19, 2018
"NBA Last Two Minute Report" 👨💻 @codenberg https://t.co/an1vCU3dEe via @puddingviz #dataviz pic.twitter.com/sqC2aeC32k
An important caveat is that Native American reservations in the northern plains continue to struggle. Also, as UNL's Richard Edwards told me, the ND fracking boom has had serious downsides in the form of increased crime and environmental destruction. https://t.co/Kxf1IkTEag
— Harry Stevens (@Harry_Stevens) October 18, 2018
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers
— ML Review (@ml_review) October 18, 2018
By @fredhohman @minsukkahng @PoloChau
Bloghttps://t.co/2c1IUTYI8v
Paperhttps://t.co/acP2GVlE57 pic.twitter.com/OFmHxwjml9
Scatterplot "trick" that I like: use the alpha channel if you have overlapping points. Makes it a lot easier to judge the density of points. pic.twitter.com/LcV9Sq9ofG
— Erik Bernhardsson (@fulhack) October 18, 2018
As our overall scoreboard of success, we're projecting the *population* that will be in states governed by each party. No offense to Wyoming and Vermont, but who's governor of California and Texas is way more important. Democrats project to govern about 60% of the population. pic.twitter.com/XbguidHbwk
— Nate Silver (@NateSilver538) October 17, 2018
One dataset, visualized with 14 different charts. Let the questions guide you. https://t.co/FVSr6fBGFS pic.twitter.com/kjpFyPmPiE
— Nathan Yau (@flowingdata) October 17, 2018
ICYMI: ⭐️, thorough code-through by @krstoffr
— Mara Averick (@dataandme) October 17, 2018
"Estimating treatment effects and ICCs from (G)LMMs on the observed scale using Bayes, Pt 1: lognormal models" https://t.co/5xUpiSrIlO #rstats #statistics #dataviz pic.twitter.com/bVxuuXQ3Yj
⏰😶 which ones, and when…
— Mara Averick (@dataandme) October 16, 2018
❓ "How we use emojis" ✏️ Jacob Gepphttps://t.co/c8viq3OrCf #rstats via @statworx pic.twitter.com/aKHBWHLHmq
🌟 step-by-step:
— Mara Averick (@dataandme) October 16, 2018
"Animated Population Pyramids in R" 👨💻 @kjhealyhttps://t.co/fHIVccMlx7 #rstats #dataviz #ggplot2 pic.twitter.com/JF492zqhF6
Did you hear about our new open-source JupyterLab extension for editing Plotly charts through a user-friendly point-and-click interface? 🤓👊 Learn how to power up your charts at our next webinar: https://t.co/qP5nkJsGGA pic.twitter.com/bw7QIbrJhx
— plotly (@plotlygraphs) October 16, 2018
Optimized bubble tea consumption by @kristw. Because it's the type of analyses we need these days https://t.co/87U4HxWtX8
— Nathan Yau (@flowingdata) October 16, 2018