[
{
"path": "README.md",
"content": "# Companies, Officials and NGO Using R\n\nIn case you need it, a curated list of testimonies / blogposts / packages from entreprises, officials and NGO using R in production and/or for research.\n\nFeel free to contribute.\n\n## Airbnb \n\n+ [Using R packages and education to scale Data Science at Airbnb](https://medium.com/airbnb-engineering/using-r-packages-and-education-to-scale-data-science-at-airbnb-906faa58e12d)\n\n\n\n+ [Using googlesheets and mailR packages in R to automate reporting](https://medium.com/airbnb-engineering/using-googlesheets-and-mailr-packages-in-r-to-automate-reporting-c09579e0377f) \n\n+ [How R helps Airbnb make the most of its data](https://peerj.com/preprints/3182.pdf)\n\n
\n\n## Amazon Web Services\n\n+ [Containerized applications with R to identify customers who need additional onboarding assistance and to detect fraud](https://earlconf.com/_downloads/london_speakers/EARL2018_-_London_-_Dzidas_Martinatis.pdf)\n\n
\n\n## BBC \n\n+ [Every story in the world has one of theses six basic plots](http://www.bbc.com/culture/story/20180525-every-story-in-the-world-has-one-of-these-six-basic-plots) \n\n+ [Nine facts about how long we live](https://www.bbc.com/news/health-43726436)\n\n\n\n+ [How the BBC Visual and Data Journalism team works with graphics in R](https://medium.com/bbc-visual-and-data-journalism/how-the-bbc-visual-and-data-journalism-team-works-with-graphics-in-r-ed0b35693535)\n\n#### Cookbook \n\n! [BBC Visual and Data Journalism cookbook for R graphics](https://bbc.github.io/rcookbook/)\n\n#### Packages\n\n+ [bbplot - R package that helps create and export ggplot2 charts in the style used by the BBC News data team](https://github.com/bbc/bbplot)\n=======\n
\n\n\n## Booking\n\n+ [How Booking.com increases the power of online experiments with CUPED](https://booking.ai/how-booking-com-increases-the-power-of-online-experiments-with-cuped-995d186fff1d)\n\n
\n\n## Province of British Columbia\n\n+ [Content (slide decks etc) from presentations related to use of R (#rstats) in the B.C. government ](https://github.com/bcgov/bcgov-rstats-public-presentations)\n\n+ [Presentation materials from bcgov useR days](https://github.com/bcgov/bcgov-useR)\n\n+ Example repo: [CANSIM-dataviewer](https://github.com/bcgov/CANSIM-dataviewer) with the code for the extraction, tabulation, and visualisation of data from Statistics Canada's CANSIM database\n\n![](\"https://github.com/bcgov/CANSIM-dataviewer/blob/master/scr/Mfg_plot.png\")
\n\n#### Packages \n\n+ [bcmaps](https://github.com/bcgov/bcmaps), an R package of map layers for British Columbia \n\n![](\"https://github.com/bcgov/bcmaps/blob/master/tools/readme/bcmaps-sticker.png\")
\n\n
\n\n## Buzzfeed \n\n+ [Using BuzzFeed’s listicle format to tell stories with maps and charts](http://www.storybench.org/using-buzzfeeds-listicle-format-tell-stories-maps-charts/)\n\n+ [How Trump’s Tweets Shaped A Year In Politics](https://www.buzzfeed.com/peteraldhous/trump-twitter-wars) - [The R code](https://buzzfeednews.github.io/2018-01-trump-twitter-wars/)\n\n+ [How A Booming Population And Climate Change Made California’s Wildfires Worse Than Ever](https://www.buzzfeed.com/peteraldhous/california-wildfires-people-climate)\n\n
\n\n## City of Chicago \n\n+ [Forecasting Chicago's Beach Water Quality](http://chicago.github.io/clear-water/)\n\n+ [Behind the Scenes: Foodborne Chicago](http://www.smartchicagocollaborative.org/behind-the-scenes-foodborne-chicago/)\n\n
\n\n## Dyson\n\n+ [Forecasting the expected sales of new models of vacuum cleaners, hand dryers, and other products](https://earlconf.com/_downloads/london_speakers/EARL2018_-_London_-_Dan_Erben.pdf)\n\n
\n\n## Ebay\n\n+ [How eBay scales R training for a global workforce](https://assets.datacamp.com/groups/case-studies/Ebay.pdf)\n\n\n
\n\n## The Economist\n\n+ [The Big Mac index](https://www.economist.com/news/2018/07/11/the-big-mac-index)\n\n
\n\n## Facebook\n\n+ [Visualizing Friendships](https://www.facebook.com/notes/facebook-engineering/visualizing-friendships/469716398919) \n\n+ [Criss-Crossing the Org Chart — Predicting Colleague Interactions with R](https://www.r-project.org/conferences/useR-2010/slides/Sun.pdf)\n\n+ [What’s on your mind?](https://www.facebook.com/notes/facebook-data-team/whats-on-your-mind/477517358858)\n\n\n\n+ [Showing Support for Marriage Equality on Facebook](https://www.facebook.com/notes/facebook-data-science/showing-support-for-marriage-equality-on-facebook/10151430548593859) \n\n+ [The Formation of Love](https://www.facebook.com/notes/facebook-data-science/the-formation-of-love/10152064609253859)\n\n#### Packages\n\n+ [Prophet — Forecasting at scale](https://facebook.github.io/prophet/)\n\n
\n\n## Financial Times \n\n+ [Is Russia-Saudi Arabia the worst World Cup game ever?](https://www.ft.com/content/e4a5012e-6e3e-11e8-92d3-6c13e5c92914)\n\n\n\n
\n\n## Kickstarter \n\n+ [10,000 Successful Projects](https://www.kickstarter.com/blog/10000-successful-projects)\n\n
\n\n## Google \n\n+ [Large-Scale Parallel Statistical Forecasting Computations in R](https://research.google.com/pubs/pub37483.html)\n\n+ [RLint: Reformatting R Code to Follow the Google Style Guide](https://research.google.com/pubs/pub42577.html)\n\n+ [R for Marketing Research and Analytics](https://research.google.com/pubs/pub43342.html)\n\n+ [RAPPOR: Privacy-Preserving Reporting Algorithms](https://github.com/google/rappor)\n\n+ [Predicting the Present with Google Trends](https://static.googleusercontent.com/media/www.google.com/fr//googleblogs/pdfs/google_predicting_the_present.pdf)\n\n#### Packages \n\n+ [abpackage - An R package for AB testing leveraging pre-period information](https://github.com/google/abpackage)\n\n+ [CausalImpact - An R package for causal inference in time series](https://github.com/google/CausalImpact)\n\n+ [MAB — R package for Multi-Armed Bandit Simulation Study](https://github.com/google/MAB)\n\n
\n\n## Indiana \n\n+ [How the State of Indiana uses R and Azure to forecast employment](http://blog.revolutionanalytics.com/2016/12/state-of-indiana-employment.html)\n\n
\n\n## John Deere\n\n+ [Order Fulfillment Forecasting at John Deere: How R Facilitates Creativity and Flexibility](https://www.slideshare.net/RevolutionAnalytics/order-fulfillment-forecasting-at-john-deere-how-r-facilitates-creativity-and-flexibility)\n\n
\n\n## Le Parisien\n\n+ [Everything you need to know about your national football team](http://leparisien.fr/sports/football/coupe-du-monde/coupe-du-monde-2018-ce-qu-il-faut-savoir-sur-la-france-01-12-2017-7426749.php)\n\n\n\n
\n\n## Microsoft\n\n+ [Microsoft R Open](https://mran.microsoft.com/open)\n\n+ [TrueSkill(TM): A Bayesian Skill Rating System](https://www.microsoft.com/en-us/research/publication/trueskilltm-a-bayesian-skill-rating-system)\n\n+ [What does Microsoft do with R?](http://blog.revolutionanalytics.com/2018/02/what-does-microsoft-do-with-r.html)\n\n+ [Personalised Marketing at Scale with Propensity Models using R and Spark](https://earlconf.com/_downloads/london_speakers/EARL2018_-_London_-_Paul_Swiontkowski.pdf)\n\n
\n\n## Mozilla\n\n+ [Understanding Private Browsing](https://blog.mozilla.org/metrics/2010/08/23/understanding-private-browsing/)\n\n\n
\n\n## N Brown Group\n\n+ [Analyze online product reviews from customers](https://earlconf.com/_downloads/london_speakers/EARL2018_-_London_-_Chris_Billingham.pdf)\n\n
\n\n## Nature\n\n+ [Bitcoin emissions alone could push global warming above 2°C](https://www.nature.com/articles/s41558-018-0321-8)\n\n
\n\n## Netpeak Group \n\n+ [Migrating from AdWords API to Google Ads API. A Comprehensive Guideline](https://netpeak.net/blog/migrating-from-adwords-api-to-google-ads-api-a-comprehensive-guideline/)\n\n+ [How to Extract Marketing Campaign Statistics from Facebook API Using R](https://netpeak.net/blog/how-to-extract-marketing-campaign-statistics-from-facebook-api-using-r/)\n\n+ [How we implemented BI analytics in contextual advertising department](https://netpeak.net/blog/how-we-implemented-bi-analytics-in-contextual-advertising-department/)\n\n#### Packages \n \n+ [getProxy - Get Free Proxy IP and Port](https://github.com/cran/getProxy)\n \n+ [rappsflyer - Work with AppsFlyer API](https://github.com/cran/rappsflyer)\n \n+ [rfacebookstat - Load Data from Facebook Marketing API](https://github.com/cran/rfacebookstat)\n \n+ [rgoogleads - Loading Data from Google Ads API](https://github.com/cran/rgoogleads)\n \n+ [rmytarget - Load Data from MyTarget API v2](https://github.com/cran/rmytarget)\n \n+ [rvkstat - R Interface to vk.com API](https://github.com/cran/rvkstat)\n \n+ [ryandexdirect - Load Data From Yandex Direct](https://github.com/cran/ryandexdirect)\n \n+ [rym - R Interface to Yandex Metrica API](https://github.com/cran/rym)\n \n+ [timeperiodsR - Simple Definition Of Time Intervals](https://github.com/cran/timeperiodsR)\n\n+ [serpstatr - Serpstat API Wrapper](https://github.com/cran/serpstatr)\n\n
\n\n## New York Times \n\n+ [The Upshot — A New York Times website with analysis and data visualizations about politics, policy and everyday life.](https://github.com/TheUpshot)\n\n
\n\n## Netflix \n\n+ [Moving from prototype to production in R](http://bryangal.vin/useR-2018/)\n\n
\n \n## Pinnacle \n\n+ [Using ‘R’ for betting analysis](https://www.pinnacle.com/en/betting-articles/Betting-Strategy/r-betting-analysis/N7Y2W3F87V489ZDC)\n\n+ [How R is driving sports betting innovation](https://www.pinnacle.com/en/betting-articles/educational/r-betting-innovation/A642DKMEXWMMKU6B)\n\n
\n \n \n\n## NHS-R Community\n\n+ [The NHS-R Community exists to support the all NHS organisations in R](https://nhsrcommunity.com/)\n\n
\n\n\n\n## StackExchange/StackOverflow\n\n+ [One year as a Data scientist at SO - David Robinson](http://varianceexplained.org/r/year_data_scientist/)\n+ [Text Mining of Stack Overflow Questions](https://stackoverflow.blog/2017/07/06/text-mining-stack-overflow-questions/)\n+ [Understanding PCA using Shiny and Stack Overflow data](https://www.rstudio.com/resources/videos/understanding-pca-using-shiny-and-stack-overflow-data/)\n+ [ne year as a Data scientist at Stack Overflow - Julia Silge](https://juliasilge.com/blog/one-year-at-stack/)\n\n
\n\n## Stitchfix \n\n+ [R in pRoduction: theRe be dRagons!](https://multithreaded.stitchfix.com/blog/2017/06/15/beware-r-in-production/) \n\n+ [Data Exploration with Weight of Evidence and Information Value in R](https://multithreaded.stitchfix.com/blog/2015/08/13/weight-of-evidence/)\n\n
\n\n## Süddeutsche Zeitung\n\n+ [data journalism with R at Süddeutsche Zeitung](https://github.com/sueddeutsche/rladies-presentation/blob/master/rladies-presentation-brunner-schories.pdf)\n\n
\n\n## T-Mobile \n\n+ [Enterprise Web Services with Neural Networks Using R and TensorFlow](https://opensource.t-mobile.com/blog/posts/r-tensorflow-api/)\n\n+ [R can API and So Can You!](https://medium.com/tmobile-tech/r-can-api-c184951a24a3)\n\n+ [Using docker to deploy an R plumber API](https://medium.com/tmobile-tech/using-docker-to-deploy-an-r-plumber-api-863ccf91516d)\n\n
\n\n## USMA\n\n+ [R in USMA](https://www.youtube.com/embed/Npk-cfQVqKo)\n\n
\n\n## Twitter\n\n+ [The geography of Tweets](https://blog.twitter.com/official/en_us/a/2013/the-geography-of-tweets.html)\n\n#### Packages \n\n+ [AnomalyDetection R package](https://github.com/twitter/AnomalyDetection)\n\n\n\n
\n\n## Uber\n\n+ [R at Uber](https://capetown2017.satrdays.org/talks/satRday-2017-van-heerden.pdf)\n\n
\n\n## UNHCR \n\n+ [UNHCR R data Package](https://github.com/unhcr/unhcrdatapackage)\n\n+ [A package for survey data crunching](https://unhcr.github.io/koboloadeR/docs/)\n\n+ [Initiated a community of data analysis with R: humanitaRian useR group](https://humanitarian-user-group.github.io/)\n\n
\n\n## United Kingdom Government \n\n+ [Transforming the process of producing official statistics](https://dataingovernment.blog.gov.uk/2017/11/27/transforming-the-process-of-producing-official-statistics/)\n\n+ [Reproducible Analytical Pipelines](https://dataingovernment.blog.gov.uk/2017/03/27/reproducible-analytical-pipeline/)\n\n
\n\n## Uptake\n\n+ [Data scientists making their code public? So crazy it just might work](https://www.uptake.com/blog/data-scientists-making-their-code-public-so-crazy-it-just-might-work)\n+ [cran-server: a lightweight, open-source way to run a custom R package server](https://github.com/uptake/cran-server)\n+ [pkgnet: R package to analyze R packages with graph theory](https://github.com/uptake/pkgnet)\n+ [updraft: parallelize processing DAGs in pure R code](https://github.com/uptake/updraft)\n+ [uptasticsearch: an R data frame client for Elasticsearch](https://github.com/uptake/uptasticsearch)\n\n\n\n
\n\n## Wikimedia \n\n+ [How we made that net neutrality clickstream diagram](https://blog.wikimedia.org/2018/01/18/on-that-net-neutrality-clickstream-diagram/)\n\n\n\n+ [Wikidata Concepts Monitor (WDCM): R in action across Big Wikidata](https://upload.wikimedia.org/wikipedia/commons/7/7c/GMilovanovic_eRum2018.pdf)\n\n
\n\n## Worldbank \n\n+ [The 2018 Atlas of Sustainable Development Goals: an all-new visual guide to data and development](http://blogs.worldbank.org/opendata/2018-atlas-sustainable-development-goals-all-new-visual-guide-data-and-development)\n\n\n"
}
]