open sourcing all of this as part of TensorFlow so that anyone can use these tools to explore their data.
for - tensorflow - data visualization of words - question - tensorflow - for SRG tool?
open sourcing all of this as part of TensorFlow so that anyone can use these tools to explore their data.
for - tensorflow - data visualization of words - question - tensorflow - for SRG tool?
for - data visualization - words in high dimensional space - Google tensorflow - open source data visualization - of words
for - chalmers university - digital twin cities centre - from - youtube - urban data visualization using mixed reality - https://hyp.is/ptvO5BexEfC063-4BZXD-A/www.youtube.com/watch?v=tN2_TJ1ZYhQ
for - mixed reality 3d graph data visualization - skyrails - gelphi
Our diagrams and charts make it easy to see where every dollar of your hard-earned money is flowing, so you can track your spending patterns at a glance.
Software and applications for creating visualizations of zettelkasten contents: - Tinderbox (Mac) - Apple's Freeform (app) - Obsidian Canvas - Excalidraw (plugin for Obsidian) - Scrintal - Heptabase - Card Buddy (Mac) - AFFiNE (https://github.com/toeverything/AFFiNE)
ZenHub’s Issue dependencies not only help teams visualize relationships between pieces of work, but they save team members a lot of time that would otherwise be lost just hunting down information.
There are two main reasons to use logarithmic scales in charts and graphs.
The data values are spread out better with the logarithmic scale. This is what I mean by responding to skewness of large values.
In Figure 2 the difference is multiplicative. Since 27 = 26 times 2, we see that the revenues for Ford Motor are about double those for Boeing. This is what I mean by saying that we use logarithmic scales to show multiplicative factors
One reason for choosing a dot plot rather than a bar chart is that it is less cluttered. We will be learning other benefits of dot plots in this and future posts.
A dot plot is judged by its position along an axis; in this case, the horizontal or x axis. A bar chart is judged by the length of the bar. I don’t like using lengths with logarithmic scales. That is a second reason that I prefer dot plots over bar charts for these data.
Data Viz with Python and RLearn to Make Plots in Python and R
data viz with python and R
An independent initiative made by Owen Cornec who has also made many other beautiful data visualizations. Wikiverse vividly captures the fact that Wikipedia is a an awe-inspiring universe to explore.
80% of data analysis is spent on the process of cleaning and preparing the data
Imagine having unnecessary and wrong data in your document, you would most likely have to experience the concept of time demarcation -- the reluctance in going through every single row and column to eliminate these "garbage data". Clearly, owning all kinds of data without organizing them feels like stuffing your closet with clothes that you should have donated 5 years ago. It is a time-consuming and soul-destroying process for us. Luckily, in R, we have something in R called "tidyverse" package, which I believe the author talks about in the next paragraph, to make life easier for everyone. I personally use dplyr and ggplot2 when I deal with data cleaning, and they are extremely helpful. WIthout these packages' existence, I have no idea when I will be able to reach the final step of data visualization.
Recognizing that the CEC hyperthreat operates at micro and macro scales across most forms of human activity and that a whole-of-society approach is required to combat it, the approach to the CEC hyperthreat partly relies on a philosophical pivot. The idea here is that a powerful understanding of the CEC hyperthreat (how it feels, moves, and operates), as well as the larger philosophical and survival-based reasons for hyper-reconfiguration, enables all actors and groups to design their own bespoke solutions. Consequently, the narrative and threat description act as a type of orchestration tool across many agencies. This is like the “shared consciousness” idea in retired U.S. Army general Stanley A. McChrystal’s “team of teams” approach to complexity.7 Such an approach is heavily dependent on exceptional communication of both the CEC hyperthreat and hyper-response pathways, as well as providing an enabling environment in terms of capacity to make decisions, access information and resources. This idea informs Operation Visibility and Knowability (OP VAK), which will be described later.
Such an effort will require a supporting worldwide digital ecosystem. In the recent past, major evolutionary transitions (MET) (Robin et al, 2021) of our species have been triggered by radical new information systems such as spoken language, and then inscribed language. Something akin to a Major Competitive Transitions (MCT) may be required to accompany a radical transition to a good anthropocene. (See annotation: https://hyp.is/go?url=https%3A%2F%2Fwww.frontiersin.org%2Farticles%2F10.3389%2Ffevo.2021.711556%2Ffull&group=world)
If large data is ingested into a public Indyweb, because Indyweb is naturally a graph database, a salience landscape can be constructed of the hyperthreat and data visualized in its multiple dimensions and scales.
Metaphorically, it can manifest as a hydra with multiple tentacles reach out to multiple scales and dimensions. VR and AR technology can be used to expose the hyperobject and its progression.
The proper hyperthreat is not climate change alone, although that is the most time sensitive dimension of it, but rather the totality of all blowbacks of human progress...the aggregate of all progress traps that have been allowed to grow, through a myopic prioritization of profit over global wellbeing due to the invisibility of the hyperobject, from molehills into mountains.
Adam Kucharski on Twitter: "Interesting visualisation of COVID-related data sharing. (2021, March 26). Ttps://t.co/lOc1mzeiHt via @OYCar https://t.co/Im9SWlCA3Q [Tweet]. @AdamJKucharski. https://twitter.com/AdamJKucharski/status/1375350545393840130
Trevor Bedford. (2022, January 10). Given ~680k cases per day, this would in turn suggest 0.8% or 1% of the US being infected with SARS-CoV-2 every day. This would translate to perhaps 5% or 10% of individuals currently infected with SARS-CoV-2 in the US. 15/15 [Tweet]. @trvrb. https://twitter.com/trvrb/status/1480610448563060738
ReconfigBehSci. (2022, January 10). RT @GeraldGmboowa: Genomic epidemiology of SARS-CoV-2 in Africa focused on different 🌍regions @AfricaCDC https://bit.ly/3tcDuJl. Using A… [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1480595472834338827
Professor Susan Michie. (2021, December 27). We (UK) don’t have to be here: It’s a political (and harmful) choice. Https://t.co/gIL3bmA17i [Tweet]. @SusanMichie. https://twitter.com/SusanMichie/status/1475436150420656131
Yaniv Erlich on Twitter. (n.d.). Twitter. Retrieved February 8, 2022, from https://twitter.com/erlichya/status/1482847821397176325
Adam Kucharski. (2022, February 8). Below figure being widely shared (from: Https://cdc.gov/mmwr/volumes/71/wr/mm7106e1.htm), but think it’s important to include uncertainty (i.e. 95% confidence intervals) when reporting estimates: Cloth mask: 56% (-17%-83%) lower odds than no mask Surgical mask: 66% (10%-87%) N95/KN95: 83% (36%-95%) https://t.co/SkPhF7CAJf [Tweet]. @AdamJKucharski. https://twitter.com/AdamJKucharski/status/1490946644837543938
Jorge A. Caballero, MD (jorgecaballero.eth). (2022, January 25). I’m not sure what to say anymore https://t.co/wapOCaoD6X [Tweet]. @DataDrivenMD. https://twitter.com/DataDrivenMD/status/1485914512360235010
Infectious Diseases. (2022, January 26). In France, a recent rise in hospitalizations raises the concern that BA.2 may not just be the harmless wake of BA.1’s powerboat Yellow line—Hospital admission Black line—Death in hospital Red line—ICU admission [Tweet]. @InfectiousDz. https://twitter.com/InfectiousDz/status/1486306246823391237
Zimmerman, M. I., Porter, J. R., Ward, M. D., Singh, S., Vithani, N., Meller, A., Mallimadugula, U. L., Kuhn, C. E., Borowsky, J. H., Wiewiora, R. P., Hurley, M. F. D., Harbison, A. M., Fogarty, C. A., Coffland, J. E., Fadda, E., Voelz, V. A., Chodera, J. D., & Bowman, G. R. (2021). SARS-CoV-2 simulations go exascale to predict dramatic spike opening and cryptic pockets across the proteome. Nature Chemistry, 13(7), 651–659. https://doi.org/10.1038/s41557-021-00707-0
Mike Honey 💉💉💉. (2022, January 22). Here’s the latest variant picture for BA.2 (Omicron). Globally it has been far less common than it’s sibling BA.1 lineage. The frequency of BA.2 is rising rapidly in several countries, notably India, Denmark & Singapore. 🧵 https://t.co/nE926hn9ws [Tweet]. @MikeHoney. https://twitter.com/Mike_Honey_/status/1484707779327950855
casey briggs. (2022, January 22). Both Victoria and New South Wales are seeing continued improvement in COVID-19 hospitalisation https://t.co/O9rB6rqeIV [Tweet]. @CaseyBriggs. https://twitter.com/CaseyBriggs/status/1485013320336052227
James 💙 Neill - 😷 🇪🇺🇮🇪🇬🇧🔶. (2021, December 30). @dgurdasani1 And for age 0-5... Https://t.co/ve3v92iJgR [Tweet]. @jneill. https://twitter.com/jneill/status/1476701258392211456
Dr. Cecília Tomori. (2021, December 27). Maryland—Just awful to watch what’s unfolding. Now at 1714 hospitalizations ⬆️ 130 in 24 hrs. 16.5% test positivity. Some counties have acted but no statewide 😷 policy! No measures to slow the spread. Https://coronavirus.maryland.gov https://t.co/C03cSRO2AX [Tweet]. @DrTomori. https://twitter.com/DrTomori/status/1475503877977948166
Jorge A. Caballero, MD. (2021, December 30). 544 children with #COVID19 were admitted to U.S. hospitals yesterday—This shattered the previous single-day record that was set 2 days ago (421) source: HHS (https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/g62h-syeh) https://t.co/bOUylcyZlV [Tweet]. @DataDrivenMD. https://twitter.com/DataDrivenMD/status/1476357620550148100
Kit Yates. (2022, January 4). There are sone issues with data from Wales and Northern Ireland covering the holiday weekend, but still, wow. U.K. breaches the 200k daily cases mark for the first time. Https://t.co/k5P96LeiRU [Tweet]. @Kit_Yates_Maths. https://twitter.com/Kit_Yates_Maths/status/1478414522205577224 i
Kit Yates. (2022, January 5). I can tell you for a fact that it isn’t ‘mild’ for everyone. Https://t.co/9DJHOMBv7F [Tweet]. @Kit_Yates_Maths. https://twitter.com/Kit_Yates_Maths/status/1478651876329594882
Alison Buttenheim. (2022, January 13). How many more days until Rhode Island’s cases line exceeds the word “exceeds” in the text header? 🙁 https://t.co/DFjqjHXutJ [Tweet]. @abuttenheim. https://twitter.com/abuttenheim/status/1481738740318015492
David Spiegelhalter. (2022, January 6). Good news: Admissions for flu not quite as tiny as last year, but close. Https://gov.uk/government/statistics/national-flu-and-covid-19-surveillance-reports-2021-to-2022-season https://t.co/YILvkQ4Vqu [Tweet]. @d_spiegel. https://twitter.com/d_spiegel/status/1479139047515856901
Ariel Karlinsky. (2022, January 2). Russia at 1.04 MILLION excess deaths since March 2020, which is about 240% higher than their reported COVID-19 deaths. This is 1st place worldwide (for countries with data) in absolute excess mortality, 2nd place on per capita terms and 9th on p-score. #poptwitter #epitwitter https://t.co/aLBRRht3z2 [Tweet]. @ArielKarlinsky. https://twitter.com/ArielKarlinsky/status/1477531141510946818
Welcome to the Australian Crisis Mobility Portal. (n.d.). Mobility-Aus. Retrieved January 10, 2022, from https://rsbyrne.github.io/mobility-aus/
Diego Bassani, PhD 🏠😷 💉 💉 💉. (2022, January 7). Seasonality, huh? Https://t.co/WcarGXqRSY [Tweet]. @DGBassani. https://twitter.com/DGBassani/status/1479278943328944130
Andrew Account for lags Kunzmann. (2021, December 28). @ProfMattFox Fatalism can be fatal https://t.co/fa4mgVn3OZ [Tweet]. @1987Andrewk. https://twitter.com/1987Andrewk/status/1475825206564376579
Trisha Greenhalgh. (2021, December 27). This is nothing short of scandalous. Unless and until those leading the public health response acknowledge the AIRBORNE nature of the virus and give transmission mitigation advice commensurate with how airborne viruses spread, we will be yo-yoing from wave to wave ad infinitum. [Tweet]. @trishgreenhalgh. https://twitter.com/trishgreenhalgh/status/1475502337594646528
Travelling Tabby. (2021, December 20). Https://travellingtabby.com/scotland-coronavirus-tracker/ There were over 6,700 new cases reported today, which is one of the highest days we’ve had. And a positivity rate of over 15% too, which is the joint highest we’ve had since reporting began. #covid19scotland #coronavirusscotland #DailyCovidUpdate https://t.co/ZvrVGc2J3I [Tweet]. @TravellingTabby. https://twitter.com/TravellingTabby/status/1472952525544255489
Colin Davis. (2021, December 20). Update for 20th Dec. The trend line still reflects 1.8 day doubling (it’s 1.7 days if we look at just the last week). Today’s number is down, but I wouldn’t read too much into that at this point. Https://t.co/kOCjxhRbop [Tweet]. @ProfColinDavis. https://twitter.com/ProfColinDavis/status/1472969632705392640
Benjy Renton. (2021, December 14). New data from CDC finds that the Omicron variant represented 2.9% of new cases in the US last week. Https://covid.cdc.gov/covid-data-tracker/#variant-proportions https://t.co/AqM8a1vekm [Tweet]. @bhrenton. https://twitter.com/bhrenton/status/1470765699907870729
Tom Moultrie. (2021, December 17). A 1-figure Gauteng update, bringing in data through Wednesday 15/12 (PCR only; by date of collection). The turn continues. On similar metrics (not shown) ALL northern provinces (NW, GT, MP, LP) seem to have now turned. Https://t.co/6Bh3kZsooK [Tweet]. @tomtom_m. https://twitter.com/tomtom_m/status/1471723711287996416
Carl Zimmer. (2021, December 15). Connecticut has gone practically vertical https://nytimes.com/interactive/2021/us/covid-cases.html?referringSource=articleShare https://t.co/mBlybyTpAA [Tweet]. @carlzimmer. https://twitter.com/carlzimmer/status/1470986172583317506
Theo Sanderson. (2021, December 16). 71.9% of cases in London with specimens from 13 December were Omicron. Overall London cases are already reaching the maximum values ever seen in the pandemic. Https://t.co/CJF5kQqBpl [Tweet]. @theosanderson. https://twitter.com/theosanderson/status/1471537690650812420
Eric Topol. (2021, December 14). Graph of Pfizer 3rd shot (booster) vs Omicron symptomatic infection, restoring to 75% protection, significantly less compared to its effect vs Delta (95%) with 95% CI, @UKHSA data, vs unvaccinated https://ft.com/content/8a6a0ec8-fd07-49cd-a3f5-386a06269a5c by @hannahkuchler @donatopmancini @mroliverbarnes https://t.co/PHMDZGIgDj [Tweet]. @EricTopol. https://twitter.com/EricTopol/status/1470744717398720513
Max Roser. (2021, December 11). The number of confirmed COVID cases is rising in all of Southern Africa. Https://t.co/3hP7f3zoqt [Tweet]. @MaxCRoser. https://twitter.com/MaxCRoser/status/1469634777078710274
💉💉 Henry Madison DPhil. (2021, December 12). Denmark, already up shit creek because of Delta, has just met Omicron. Near-vertical growth. #auspol #covid19aus https://t.co/Jhvs3dWWhK [Tweet]. @RageSheen. https://twitter.com/RageSheen/status/1470125914788818944
Dave Keating. (2021, December 8). Boris Johnson’s continued pretence that UK is one of the most vaccinated countries in the world, repeated again in press conference just now announcing new restrictions, is getting tiresome. That has not been the case for many many months, despite 🇬🇧🇺🇸 vaccine hoarding early on. Https://t.co/tQt6aXGtNI [Tweet]. @DaveKeating. https://twitter.com/DaveKeating/status/1468655107436802052
Alistair Haimes. (2021, December 3). @nicfreeman1209 Ok, so vax take-up in Gauteng is 38.6%. Given 9% of inpatients whose vax status is known are vaxxed, I think that’s pretty encouraging (odds, log odds, etc.) https://t.co/eAAfIQ8BQT [Tweet]. @AlistairHaimes. https://twitter.com/AlistairHaimes/status/1466711359329120258
Lindiwe Mazibuko. (2021, November 27). When literally every country “banning” you has a higher infection rate 🙄 https://t.co/NZMuf9Pfx5 [Tweet]. @LindiMazibuko. https://twitter.com/LindiMazibuko/status/1464539078611939333
News, B. N. O. (2021, November 26). Tracking COVID-19 variant Omicron. BNO News. https://bnonews.com/index.php/2021/11/omicron-tracker/
Jorge A. Caballero, MD. (2021, December 3). #Omicron is sending more kids to the hospital than #Delta in South Africa https://t.co/bv5CxIag2u [Tweet]. @DataDrivenMD. https://twitter.com/DataDrivenMD/status/1466658311227404292
Paul Mainwood. (2021, November 29). @mroliverbarnes If it’s anything like Beta, then boosters should clobber it just fine. Https://t.co/LPX0GAXn1y [Tweet]. @PaulMainwood. https://twitter.com/PaulMainwood/status/1465263524104609792
Art Poon. (2021, November 28). Our first https://filogeneti.ca/CoVizu update with B.1.1.529. As expected, number of mutations is well over molecular clock prediction (~13 diffs). Relatively low numbers of identical genomes implies large number of unsampled infections. We update every two days from GISAID. https://t.co/m8w2CjL1c0 [Tweet]. @art_poon. https://twitter.com/art_poon/status/1465001066194481162
Andrew L. Croxford. (2021, December 1). Switzerland just clocked 10,466 cases today, which normalised to the U.K. would be 81,500, with a positive test frequency of 15.83%. Https://t.co/fxjSaL9n3O [Tweet]. @andrew_croxford. https://twitter.com/andrew_croxford/status/1466034479156404226
gianluca c 🏴☠️🇻🇪 #TeamFauci #MaskUp #no GBD. (2021, November 29). Gauteng just updated 47 week and its shit https://t.co/yu5aLzwoJE [Tweet]. @gianlucac1. https://twitter.com/gianlucac1/status/1465300644336738308
Prof. Christina Pagel. (2021, November 24). Meanwhile AY.4.2 (Delta grandchild) continues its very slow path to English dominance. Makes life a bit harder by being a bit more transmissible but luckily doesn’t seem any worse than Delta in any other respect. Https://t.co/kB0V0Z66GT [Tweet]. @chrischirp. https://twitter.com/chrischirp/status/1463508172941967365
Chise 🧬🧫🦠💉🔜 MFF. (2021, November 21). If you’re wondering what difference a booster makes. Https://t.co/858ZpST7Kh [Tweet]. @sailorrooscout. https://twitter.com/sailorrooscout/status/1462441020948459525
Charles #GetCovered-ba 🩺. (2021, November 13). America 2021 in one image. Https://t.co/SuTCkCp2Pm [Tweet]. @charles_gaba. https://twitter.com/charles_gaba/status/1459565881214836743
Paul Mainwood. (2021, November 18). Holy guacamole. Https://t.co/mIcWJMHdHJ [Tweet]. @PaulMainwood. https://twitter.com/PaulMainwood/status/1461337249950404625
European Commission 🇪🇺. (2021, November 23). Data shows us that the higher the vaccination rate, the lower the death rate. #COVID19 #VaccinesWork https://t.co/mORrrQOPsj [Tweet]. @EU_Commission. https://twitter.com/EU_Commission/status/1463119478099693571
COVID-19 Living Evidence. (2021, November 12). As of 12.11.2021, we have indexed 257,633 publications: 18,674 pre-prints 238,959 peer-reviewed publications Pre-prints: BioRxiv, MedRxiv Peer-reviewed: PubMed, EMBASE, PsycINFO https://t.co/ytOhLG90Pi [Tweet]. @evidencelive. https://twitter.com/evidencelive/status/1459163720450519042
Jeffrey Barrett. (2021, October 19). Proportion of AY.4.2 (now on http://covid19.sanger.ac.uk) has been steadily increasing in England, which is a pattern that is quite different from other AY lineages. Several of them rose when there was still Alpha to displace, but none has had a consistent advantage vs other Delta. Https://t.co/mD5gQzKxgV [Tweet]. @jcbarret. https://twitter.com/jcbarret/status/1450408485829718039
BK Titanji #ILookLikeAScientist. (2021, November 2). I simply can’t get over this graph @FT https://t.co/Uozp7yBs9n [Tweet]. @Boghuma. https://twitter.com/Boghuma/status/1455493059534376963
Henk-Jan Westeneng on Twitter. (n.d.). Twitter. Retrieved November 2, 2021, from https://twitter.com/HJWesteneng/status/1455304431038308352 i
Gil Feldman. (2021, October 26). @EricTopol Updated data from Israel. The booster works, without any doubt! Red (empty battery): Un-vax Light green (half battery): 2nd dose without the booster Green (full battery): With the booster https://t.co/HbZBvDMQs6 [Tweet]. @feldman_gil. https://twitter.com/feldman_gil/status/1452845319251767299
John Roberts on Twitter: “154k booster 💉reported today in 🏴, bringing the total to 1.58m, out of 4.56m. So that’s another 3m eligible for a jab as soon as they can be scheduled in. 1/ https://t.co/tw1JmrOiUo” / Twitter. (n.d.). Retrieved October 15, 2021, from https://twitter.com/john_actuary/status/1445785517774176262
Sam Wang on Twitter: “These are risk levels that you pose to other people. They’re compared with you as—A nonsmoker—A sober driver—A vaccinated person. Unvaccinated? 5x as likely to get sick, for 3x as long. Total risk to others? 15x a vaccinated person Details:https://t.co/ckTWaivK8n https://t.co/PhpLvX2dsm” / Twitter. (n.d.). Retrieved September 19, 2021, from https://twitter.com/SamWangPhD/status/1438361144759132167
Prof. Christina Pagel on Twitter: “THREAD latest on B.1.617.2 variant in England: B.1.617.2 (1st discovered in India) is now dominant in England. Here is a thread summarising latest PHE report and Sanger local data. TLDR: it is NOT good news. 1/7” / Twitter. (n.d.). Retrieved August 24, 2021, from https://twitter.com/chrischirp/status/1399333330286415876
John Thornhill on Twitter: “Good news: Vaccine hesitancy collapses Smart data analysis from @TheEconomist https://t.co/cQcajRtEM6 https://t.co/IWIbUsEFXG” / Twitter. (n.d.). Retrieved August 1, 2021, from https://twitter.com/johnthornhillft/status/1418510295241269248
Hiroki Sayama. (2021, May 28). Weekly update This will be the last US domestic visualization Details -> https://github.com/hsayama/COVID-19-geographical-animations https://t.co/Mz23MDaa6l [Tweet]. @HirokiSayama. https://twitter.com/HirokiSayama/status/1398344774843781128
Leising, D., Grenke, O., & Cramer, M. (2021). Visual Argument Structure Tool (VAST). PsyArXiv. https://doi.org/10.31234/osf.io/dvfq7
Conor Kelly. (2021, July 14). Correlation between vaccination coverage and COVID hospitalizations per million over time, by state https://t.co/g6AMTDXOzb [Tweet]. @CohoKelly. https://twitter.com/CohoKelly/status/1415310919266095113
BNO Newsroom. (2021, July 14). COVID-19 hospitalizations in Missouri have reached a 5-month high https://t.co/342RW903WS [Tweet]. @BNODesk. https://twitter.com/BNODesk/status/1415105797575610368
Adam Kucharski on Twitter: “As Delta spreads, cases starting to rise again across Europe... Https://t.co/mwyFVlUPVY” / Twitter. (n.d.). Retrieved July 12, 2021, from https://twitter.com/AdamJKucharski/status/1412498377619673095
Meaghan Kall 🏳️🌈 on Twitter: “The updated cumulative growth curves showing continued exponential growth of B.1.617.2.. Https://t.co/3fmEwU7cP3” / Twitter. (n.d.). Retrieved July 2, 2021, from https://twitter.com/kallmemeg/status/1397981951907217411
Helen McArdle on Twitter: “The good news: An astonishing 98.2% of over-60s in Scotland are now fully vaccinated. That’s an amazing uptake. It doesn’t mean they are 100% protected of course (and especially not when case rates are high) but their risk of hospitalisation/death is cut by over 90% https://t.co/DzAxkpLvcR” / Twitter. (n.d.). Retrieved June 30, 2021, from https://twitter.com/HMcArdleHT/status/1409821893557768195
Max Roser on Twitter: “Confirmed COVID deaths have increased very rapidly in Namibia. Https://t.co/WKZw6UsZvg” / Twitter. (n.d.). Retrieved June 30, 2021, from https://twitter.com/MaxCRoser/status/1409785445274341376
RichardBrown on Twitter: “@Richard_Florida Still pretty slow recovery in London too @nicolegelinas. Https://t.co/nH9FOpV386” / Twitter. (n.d.). Retrieved June 29, 2021, from https://twitter.com/MinorPlaces/status/1407018950714605574
Madhu Pai, MD, PhD on Twitter: “#COVID19 surge in Uganda looks ominous Vaccine coverage = 1.5% with 1 dose https://t.co/TRAjEVC59U” / Twitter. (n.d.). Retrieved June 7, 2021, from https://twitter.com/paimadhu/status/1401010082884853768
Winton Centre Cambridge. (n.d.). Retrieved May 12, 2021, from https://wintoncentre.maths.cam.ac.uk/news/latest-data-mhra-blood-clots-associated-astra-zeneca-covid-19-vaccine/
ReconfigBehSci on Twitter: ‘the SciBeh initiative is about bringing knowledge to policy makers and the general public, but I have to say this advert I just came across worries me: Where are the preceding data integrity and data analysis classes? Https://t.co/5LwkC1SVyF’ / Twitter. (n.d.). Retrieved 18 February 2021, from https://twitter.com/SciBeh/status/1362344945697308674
The Data Visualizations Behind COVID-19 Skepticism. (n.d.). The Data Visualizations Behind COVID-19 Skepticism. Retrieved March 27, 2021, from http://vis.csail.mit.edu/covid-story/
Benjy Renton on Twitter: “For those who are wondering: There is a slight association (r = 0.34) between the percentage a county voted for Trump in 2020 and estimated hesitancy levels. As @JReinerMD mentioned, GOP state, county and local levels need to do their part to promote vaccination. Https://t.co/ZY2lUqHgLd” / Twitter. (n.d.). Retrieved April 28, 2021, from https://twitter.com/bhrenton/status/1382330404586274817
Ashish K. Jha, MD, MPH. (2020, December 12). Michigan vs. Ohio State Football today postponed due to COVID But a comparison of MI vs OH on COVID is useful Why? While vaccines are coming, we have 6-8 hard weeks ahead And the big question is—Can we do anything to save lives? Lets look at MI, OH for insights Thread [Tweet]. @ashishkjha. https://twitter.com/ashishkjha/status/1337786831065264128
The COVID Tracking Project. (2020, November 19). Our daily update is published. States reported 1.5M tests, 164k cases, and 1,869 deaths. A record 79k people are currently hospitalized with COVID-19 in the US. Today’s death count is the highest since May 7. Https://t.co/8ps5itYiWr [Tweet]. @COVID19Tracking. https://twitter.com/COVID19Tracking/status/1329235190615474179
Flightradar24. (2020, November 24). The skies above North America at Noon ET on the Tuesday before Thanksgiving. Active flights 2018: 6,815 2019: 7,630 2020: 6,972 📡 https://t.co/NePPWZCDVp https://t.co/WOY9j0BXpx [Tweet]. @flightradar24. https://twitter.com/flightradar24/status/1331286193875640322
Makulec, A. (2021, February 1). Demystifying Vaccination Metrics. Medium. https://medium.com/nightingale/demystifying-vaccination-metrics-cd0a29251dd2
Treemaps are a visualization method for hierarchies based on enclosure rather than connection [JS91]. Treemaps make it easy to spot outliers (for example, the few large files that are using up most of the space on a disk) as opposed to parent-child structure.
Treemaps visualize enclosure rather than connection. This makes them good visualizations to spot outliers (e.g. large files on a disk) but not for understanding parent-child relationships.
Outbreak.info. (n.d.). Outbreak.Info. Retrieved October 25, 2020, from https://outbreak.info/
Leatherby, L. (2020, October 15). U.S. Virus Cases Climb Toward a Third Peak. The New York Times. https://www.nytimes.com/interactive/2020/10/15/us/coronavirus-cases-us-surge.html
(((Howard Forman))) on Twitter. (n.d.). Twitter. Retrieved October 12, 2020, from https://twitter.com/thehowie/status/1315418282590121984
Dr Duncan Robertson on Twitter. (n.d.). Twitter. Retrieved October 12, 2020, from https://twitter.com/Dr_D_Robertson/status/1314544108547997703
Stix, Y. Z., Gary. (n.d.). COVID-19 Is Now the Third Leading Cause of Death in the U.S. Scientific American. Retrieved October 9, 2020, from https://www.scientificamerican.com/article/covid-19-is-now-the-third-leading-cause-of-death-in-the-u-s1/
Fionna O’Leary, 🕯 on Twitter. (n.d.). Twitter. Retrieved October 6, 2020, from https://twitter.com/fascinatorfun/status/1312855480956575744
2019nCOV. (n.d.). MOBS Lab. Retrieved October 2, 2020, from https://www.mobs-lab.org/2019ncov.html
Harvard’s Chetty Finds Economic Carnage in Wealthiest ZIP Codes. (2020, September 24). Bloomberg.Com. https://www.bloomberg.com/news/features/2020-09-24/harvard-economist-raj-chetty-creates-god-s-eye-view-of-pandemic-damage
Tim spector on Twitter. (n.d.). Twitter. Retrieved September 25, 2020, from https://twitter.com/timspector/status/1308873677807792129
"The Data Visualisation Catalogue is a project developed by Severino Ribecca to create a library of different information visualisation types." I like the explanations of when one might use a particular type of data visualization to highlight - or obscure! - what the data is saying.
Carl T. Bergstrom on Twitter. (n.d.). Twitter. Retrieved September 22, 2020, from https://twitter.com/CT_Bergstrom/status/1306995362368954369
Graphs and maps from EUROMOMO. (n.d.). EUROMOMO. Retrieved September 18, 2020, from https://euromomo.eu/dev-404-page/
The COVID Tracking Project on Twitter. (n.d.). Twitter. Retrieved September 16, 2020, from https://twitter.com/COVID19Tracking/status/1304910646404739073
Krista Fischer on Twitter. (n.d.). Twitter. Retrieved September 15, 2020, from https://twitter.com/kristafischer16/status/1305145951955423233
Stuart mcdonald on Twitter. (n.d.). Twitter. Retrieved September 10, 2020, from https://twitter.com/ActuaryByDay/status/1303719422595682306
Spiegelhalter, D. (2020). Use of “normal” risk to improve understanding of dangers of covid-19. BMJ, 370. https://doi.org/10.1136/bmj.m3259
COVID-19. (n.d.). Retrieved September 7, 2020, from https://covid19.healthdata.org/united-states-of-america?view=total-deaths&tab=trend
COVID Projections Tracker. (n.d.). Retrieved September 7, 2020, from https://www.covid-projections.com/
ReconfigBehSci on Twitter: “RT @ScottGottliebMD: See how quickly you can find Sweden on this map.... https://t.co/bhXACObtnQ” / Twitter. (n.d.). Twitter. Retrieved June 29, 2020, from https://twitter.com/scibeh/status/1276799757575315457
COVID Recovery Dashboard. Retrieved from https://goodjudgment.io/covid-recovery/#1363 on 12/08/2020
Roll over each school to find out more information on their respective plans. (n.d.). Tableau Software. Retrieved August 2, 2020, from https://public.tableau.com/views/NESCACFallPlansMap/Dashboard1
Luscombe, A., & McClelland, A. (2020). Policing the Pandemic: Tracking the Policing of Covid-19 across Canada [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/9pn27
Natalie E. Dean, PhD on Twitter: “THINK LIKE AN EPIDEMIOLOGIST: There are more new confirmed cases each day in the US than at any time during the earlier April peak. But is it really meaningful to compare those numbers? How do epidemiologists decide when to sound the alarm? A thread. 1/11 https://t.co/rPelzIvcxs” / Twitter. (n.d.). Twitter. Retrieved July 3, 2020, from https://twitter.com/nataliexdean/status/1278868210385915904
Per capita: COVID-19 tests vs. Confirmed deaths. (n.d.). Our World in Data. Retrieved June 23, 2020, from https://ourworldindata.org/grapher/covid-19-tests-deaths-scatter-with-comparisons
Katz, M. MD. (2020, June 21). "Amazing what a difference four weeks makes since Memorial Day Weekend in #COVID19 New cases/day by U.S. region, adjusted for population". Twitter. https://twitter.com/subatomicdoc/status/1274702408317374466
Starr, T. N., Greaney, A. J., Hilton, S. K., Crawford, K. H., Navarro, M. J., Bowen, J. E., Tortorici, M. A., Walls, A. C., Veesler, D., & Bloom, J. D. (2020). Deep mutational scanning of SARS-CoV-2 receptor binding domain reveals constraints on folding and ACE2 binding [Preprint]. Microbiology. https://doi.org/10.1101/2020.06.17.157982
van Smeden, M. (2020, May 26). "RT @MaartenvSmeden: Often more than 300 COVID-19 related scientific articles published per day Data from @evidencelive." Twitter. https://twitter.com/SciBeh/status/1265657595307667457
Balloux, F. (2020, May 22) A thread written by @BallouxFrancois. Threader. https://threader.app/thread/1263745877702737920
Cheshire, J. (2020, May 18). "John Snow's map of cholera looked as dull as (cholera filled) dishwater compared to his competitors...His brilliance was a solid data collection & then a simple map presenting what he knew. Each death marked in black and white. Here's a lesson for COVID-19 dataviz... 1/11" Twitter. https://twitter.com/spatialanalysis/status/1262338373253042178
Andersson, L. (2020, June 08) COVID-19 i svensk intensivvård. Retrieved June 8, 2020, from https://www.icuregswe.org/data--resultat/covid-19-i-svensk-intensivvard/
Epidemiologische Abklärung am Beispiel COVID-19. (n.d.). AGES - Österreichische Agentur für Gesundheit und Ernährungssicherheit. https://www.ages.at/service/service-presse/pressemeldungen/epidemiologische-abklaerung-am-beispiel-covid-19/
Yang, F. (2020). Data Visualization for Health and Risk Communication. In H. D. O’Hair, M. J. O’Hair, E. B. Hester, & S. Geegan (Eds.), The Handbook of Applied Communication Research (1st ed., pp. 213–232). Wiley. https://doi.org/10.1002/9781119399926.ch13
Carl T. Bergstrom on Twitter
Fansher, M., Adkins, T., Lalwani, P., Quirk, M., Boduroglu, A., Lewis, R., … Jonides, J. (2020, May 19). How well do ordinary Americans forecast the growth of COVID-19?. https://doi.org/10.31234/osf.io/2d5r9
COVID-19 Modeling: Italy
The COVID Tracking Project - Twitter
Tsitsulin, A. & Perozzi B. Understanding the Shape of Large-Scale Data. (2020 May 05). Google AI Blog. http://ai.googleblog.com/2020/05/understanding-shape-of-large-scale-data.html
The above diagram shows which Linking Open Data datasets are connected, as of August 2014.
Dey, S. K., Rahman, M. M., Siddiqi, U. R., & Howlader, A. (n.d.). Analyzing the epidemiological outbreak of COVID-19: A visual exploratory data analysis approach. Journal of Medical Virology, n/a(n/a). https://doi.org/10.1002/jmv.25743
Coronavirus Pandemic (COVID-19) – the data. (n.d.). Our World in Data. Retrieved May 4, 2020, from https://ourworldindata.org/coronavirus-data
Callaghan, S. (2020). COVID-19 Is a Data Science Issue. Patterns, 100022. https://doi.org/10.1016/j.patter.2020.100022
Data visualization is both an art and a science
Get a convenient overview of your test results
For n < 5 we recommend showing the individual data points.
Source code of this (or predecessor to this): https://gist.github.com/kerryrodden/7090426
Thanks also to this example from the D3 gallery for demonstating how to create sunburst charts.
The main priorities of different ELN features
A ranked order in the plot would have been more insighful
Let’s take a look at one more visitor, Arel::Visitors::Dot. The visitor generates the Graphviz’s Dot format and we can use it to create diagrams out of an AST.
First sighting of Jupyter Notebook (that I recall).
Avoiding complicated outlining or mind-mapping software saves a bunch of mouse clicks or dreaming up complicated visualizations (it helps if you are a linear thinker).
Hmm. I'm not sure I agree with this thought/sentiment (though it's hard to tell since it's an incomplete sentence). I think visualizations and mind-mapping software might be an even better way to go, in terms of efficiency of editing (since they are specialized for the task), enjoyment of use, etc.
The main thing text files have going for them is flexibility, portability, client-neutrality, the ability to get started right now without researching and evaluating a zillion competing GUI app alternatives.
landscape vs. portrait.
slides are landscape, reports are portrait!
Material Design Material System Introduction Material studies About our Material studies Basil Crane Fortnightly Owl Rally Reply Shrine Material Foundation Foundation overview Environment Surfaces Elevation Light and shadows Layout Understanding layout Pixel density Responsive layout grid Spacing methods Component behavior Applying density Navigation Understanding navigation Navigation transitions Search Color The color system Applying color to UI Color usage Text legibility Dark theme Typography The type system Understanding typography Language support Sound About sound Applying sound to UI Sound attributes Sound choreography Sound resources Iconography Product icons System icons Animated icons Shape About shape Shape and hierarchy Shape as expression Shape and motion Applying shape to UI Motion Understanding motion Speed Choreography Customization Interaction Gestures Selection States Material Guidelines Communication Confirmation & acknowledgement Data formats Data visualization Principles Types Selecting charts Style Behavior Dashboards Empty states Help & feedback Imagery Launch screen Onboarding Offline states Writing Guidelines overview Material Theming Overview Implementing your theme Components App bars: bottom App bars: top Backdrop Banners Bottom navigation Buttons Buttons: floating action button Cards Chips Data tables Dialogs Dividers Image lists Lists Menus Navigation drawer Pickers Progress indicators Selection controls Sheets: bottom Sheets: side Sliders Snackbars Tabs Text fields Tooltips Usability Accessibility Bidirectionality Platform guidance Android bars Android fingerprint Android haptics Android icons Android navigating between apps Android notifications Android permissions Android settings Android slices Android split-screen Android swipe to refresh Android text selection toolbar Android widget Cross-platform adaptation Data visualization Data visualization depicts information in graphical form. Contents Principles Types Selecting charts Style Behavior Dashboards Principles Data visualization is a form of communication that portrays dense and complex information in graphical form. The resulting visuals are designed to make it easy to compare data and use it to tell a story – both of which can help users in decision making. Data visualization can express data of varying types and sizes: from a few data points to large multivariate datasets. AccuratePrioritize data accuracy, clarity, and integrity, presenting information in a way that doesn’t distort it. HelpfulHelp users navigate data with context and affordances that emphasize exploration and comparison. ScalableAdapt visualizations for different device sizes, while anticipating user needs on data depth, complexity, and modality. Types Data visualization can be expressed in different forms. Charts are a common way of expressing data, as they depict different data varieties and allow data comparison.The type of chart you use depends primarily on two things: the data you want to communicate, and what you want to convey about that data. These guidelines provide descriptions of various different types of charts and their use cases.Types of chartsChange over time charts show data over a period of time, such as trends or comparisons across multiple categories. Common use cases include: Category comparison...Read MoreChange over timeChange over time charts show data over a period of time, such as trends or comparisons across multiple categories.Common use cases include: Stock price performanceHealth statisticsChronologies Change over time charts include:1. Line charts 2. Bar charts 3. Stacked bar charts 4. Candlestick charts 5. Area charts 6. Timelines 7. Horizon charts 8. Waterfall charts Category comparisonCategory comparison charts compare data between multiple distinct categories. Use cases include: Income across different countriesPopular venue timesTeam allocations Category comparison charts include: 1. Bar charts 2. Grouped bar charts 3. Bubble charts 4. Multi-line charts 5. Parallel coordinate charts 6. Bullet charts RankingRanking charts show an item’s position in an ordered list.Use cases include: Election resultsPerformance statistics Ranking charts include: 1. Ordered bar charts 2. Ordered column charts 3. Parallel coordinate charts Part-to-wholePart-to-whole charts show how partial elements add up to a total.Use cases include: Consolidated revenue of product categoriesBudgets Part-to-whole charts include: 1. Stacked bar charts 2. Pie charts 3. Donut charts 4. Stacked area charts 5. Treemap charts 6. Sunburst charts CorrelationCorrelation charts show correlation between two or more variables.Use cases include: Income and life expectancy Correlation charts include: 1. Scatterplot charts 2. Bubble charts 3. Column and line charts 4. Heatmap charts DistributionDistribution charts show how often each values occur in a dataset. Use cases include: Population distributionIncome distribution Distribution charts include: 1. Histogram charts 2. Box plot charts 3. Violin charts 4. Density charts FlowFlow charts show movement of data between multiple states.Use cases include: Fund transfersVote counts and election results Flow charts include: 1. Sankey charts 2. Gantt charts 3. Chord charts 4. Network charts RelationshipRelationship charts show how multiple items relate to one other.Use cases includeSocial networksWord charts Relationship charts include: 1. Network charts 2. Venn diagrams 3. Chord charts 4. Sunburst charts Selecting charts Multiple types of charts can be suitable for depicting data. The guidelines below provide insight into how to choose one chart over another. Showing change over timeChange over time can be expressed using a time series chart, which is a chart that represents data points in chronological order. Charts that express...Read MoreChange over time can be expressed using a time series chart, which is a chart that represents data points in chronological order. Charts that express change over time include: line charts, bar charts, and area charts.Type of chartUsageBaseline value * Quantity of time seriesData typeLine chartTo express minor variations in dataAny valueAny time series (works well for charts with 8 or more time series)ContinuousBar chartTo express larger variations in data, how individual data points relate to a whole, comparisons, and rankingZero4 or fewerDiscrete or categoricalArea chartTo summarize relationships between datasets, how individual data points relate to a wholeZero (when there’s more than one series)8 or fewerContinuous* The baseline value is the starting value on the y-axis.Bar and pie chartsBoth bar charts and pie charts can be used to show proportion, which expresses a partial value in comparison to a total value. Bar charts,...Read MoreBoth bar charts and pie charts can be used to show proportion, which expresses a partial value in comparison to a total value. Bar charts express quantities through a bar’s length, using a common baselinePie charts express portions of a whole, using arcs or angles within a circleBar charts, line charts, and stacked area charts are more effective at showing change over time than pie charts. Because all three of these charts share the same baseline of possible values, it’s easier to compare value differences based on bar length. Do.Use bar charts to show changes over time or differences between categories. Don’t.Don’t use multiple pie charts to show changes over time. It’s difficult to compare the difference in size across each slice of the pie. Area chartsArea charts come in several varieties, including stacked area charts and overlapped area charts: Overlapping area charts are not recommended with more than two time...Read MoreArea charts come in several varieties, including stacked area charts and overlapped area charts:Stacked area charts show multiple time series (over the same time period) stacked on top of one another Overlapped area charts show multiple time series (over the same time period) overlapping one anotherOverlapping area charts are not recommended with more than two time series, as doing so can obscure the data. Instead, use a stacked area chart to compare multiple values over a time interval (with time represented on the horizontal axis). Do.Use a stacked area chart to represent multiple time series and maintain a good level of legibility. Don’t.Don’t use overlapped area charts as it obscures data values and reduces readability. Style Data visualizations use custom styles and shapes to make data easier to understand at a glance, in ways that suit the user’s needs and context.Charts can benefit from customizing the following: Graphical elementsTypographyIconographyAxes and labelsLegends and annotationsStyling different types of dataVisual encoding is the process of translating data into visual form. Unique graphical attributes can be applied to both quantitative data (such as temperature, price,...Read MoreVisual encoding is the process of translating data into visual form. Unique graphical attributes can be applied to both quantitative data (such as temperature, price, or speed) and qualitative data (such as categories, flavors, or expressions). These attributes include:ShapeColorSizeAreaVolumeLengthAnglePosition DirectionDensityExpressing multiple attributesMultiple visual treatments can be applied to more than one aspect of a data point. For example, a bar color can represent a category, while a bar’s length can express a value (like population size). Shape can be used to represent qualitative data. In this chart, each category is represented by a specific shape (circles, squares, and triangles), which makes it easy to compare data both within a specific range or against other categories. ShapeCharts can use shapes to display data in a range of ways. A shape can be styled as playful and curvilinear, or precise and high-fidelity,...Read MoreCharts can use shapes to display data in a range of ways. A shape can be styled as playful and curvilinear, or precise and high-fidelity, among other ways in between. Level of shape detailCharts can represent data at varying levels of precision. Data intended for close exploration should be represented by shapes that are suitable for interaction (in terms of touch target size and related
Balloon plot
Balloon plot
1RWDOOPRYLHVKDYHWREHGRFXPHQWDULHVDQGQRWDOOYLVXDOL]DWLRQKDVWREHWUDGLWLRQDOFKDUWVDQGJUDSKV
This is an interesting fact, usually when I think of visualization and data I go to the classic default charts and data. I'll have to keep this iin mind.
Nyhan and Reifler also found that presenting challenging information in a chart or graph tends to reduce disconfirmation bias. The researchers concluded that the decreased ambiguity of graphical information (as opposed to text) makes it harder for test subjects to question or argue against the content of the chart.
Amazingly important double-edged finding for discussions of data visualization!
Fig. 4
Graph is extremely unclear. Bad usage of point shapes
fast data visualization dominates the professional literature
Thus, the digital object ossifies out of two histories, one virtual and another visual.Within computation, the object arises out of a desire to create a model of the worldwithin the computer but at the same time out of an attempt to create a whole new visualworld native to the compute
After we were done, pictures were taken of the group and distributed online to groups in other cities performing similar activities, contributing to the spectacle of the day.
En los eventos locales se toman fotos durante el evento, al margen de los resultados. En el Data Week en cambio, las fotos con pocas en comparación (a veces nulas), particularmente en consideración a la privacidad. La lógica del espectáculo/impacto está más centrada en las visualizaciones mismas.
That “hackers” can model beneficial process disrupts the often presumed subversive nature of hacking as much as it does easy assumptions about a Foucaultian notion of governmentality. Prototypes act as working evidence to lobby for changing government process, particularly those that improve digital infrastructure or direct communication with citizens. The capa-bility of code to act as a persuasive argument has long been noted, and modeling can produce charged debates about the very meaning of “civic.”
[...] On a level of hackathons, prototypes can be speculative (Lodato and DiSalvo, in press) rather than an “outcome,” revealing conflicting notions of “civic tech” (Shaw, 2014).
Nuestro enfoque ha estado centrado más en la modelación, que es requerida para la visualización, pero también en la idea de construir capacidad en la infraestructura y en la comunidad, lo cual va más allá del prototipo volátil, que se abandona después.
Prophet : Facebook에서 오픈 소스로 공개한 시계열 데이터의 예측 도구로 R과 Python으로 작성되었다.
python statics opensource, also can use R
sites such as Facebook and Twitter automatically and continuously refresh the page; it’s impossible to get to the bottom of the feed.
Well is not. A scrapping web technique used for the Data Selfies project goes to the end of the scrolling page for Twitter (after almost scrolling 3k tweets), which is useful for certain valid users of scrapping (like overwatch of political discourse on twitter).
So, can be infinite scrolling be useful, but not allowed by default on this social networks. Could we change the way information is visualized to get an overview of it instead of being focused on small details all the time in an infitite scroll tread mill.
If efficiency incentives and tools have been effective for utilities, manufacturers, and designers, what about for end users? One concern I’ve always had is that most people have no idea where their energy goes, so any attempt to conserve is like optimizing a program without a profiler.
This is aimed at people in the tech industry, and is more about what you can do with your career than at a hackathon. I’m not going to discuss policy and regulation, although they’re no less important than technological innovation. A good way to think about it, via Saul Griffith, is that it’s the role of technologists to create options for policy-makers.
Nice to see this conversation happening between technology and broader socio-political problems so explicit in Bret's discourse.
What we're doing in fact is enabling this conversation between technologist and policy-makers first, and we're highlighting it via hackathon/workshops, but not reducing it only to what happens there (an interesting critique to the techno-solutionism hackathon is here), using the feedback loops in social networks, but with an intention of mobilizing a setup that goes beyond. One example is our twitter data selfies (picture/link below). The necesity of addressing urgent problem that involve techno-socio-political complex entanglements is more felt in the Global South.
^ Up | Twitter data selfies: a strategy to increase the dialog between technologist/hackers and policy makers (click here for details).
What type of team do you need to create these visualisations? OpenDataCity has a special team of really high-level nerds. Experts on hardware, servers, software development, web design, user experience and so on. I contribute the more mathematical view on the data. But usually a project is done by just one person, who is chief and developer, and the others help him or her. So, it's not like a group project. Usually, it's a single person and a lot of help. That makes it definitely faster, than having a big team and a lot of meetings.
This strengths the idea that data visualization is a field where a personal approach is still viable, as is shown also by a lot of individuals that are highly valuated as data visualizers.
Books on data science and R programming by Roger D. Peng of Johns Hopkins.
UT Austin SDS 348, Computational Biology and Bioinformatics. Course materials and links: R, regression modeling, ggplot2, principal component analysis, k-means clustering, logistic regression, Python, Biopython, regular expressions.
Python interface to the R programming language.<br> Use R functions and packages from Python.<br> https://pypi.python.org/pypi/rpy2
The effectiveness of infographics, or any other form of communication, can be measured in terms of whether people:
Titles are important. Ideally, the title should concisely state the main point you want people to grasp.
Recall of both labels and data can be improved by using redundancy -- text as well as images. For example:
the future of visualization
really true!
show data variations, not design variations