1855 search results for "RStudio"

Clandestine DNS lookups with gdns

April 10, 2016
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Clandestine DNS lookups with gdns

Google recently announced their DNS-over-HTTPS API, which “enhances privacy and security between a client and a recursive resolver, and complements DNSSEC to provide end-to-end authenticated DNS lookups”. The REST API they provided was pretty simple to wrap into a package and I tossed in some SPF functions that I had lying around to bulk it... Continue reading →

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Free data science video lecture: debugging in R

April 9, 2016
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We are pleased to release a new free data science video lecture: Debugging R code using R, RStudio and wrapper functions. In this 8 minute video we demonstrate the incredible power of R using wrapper functions to catch errors for later reproduction and debugging. If you haven’t tried these techniques this will really improve your … Continue reading...

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Safe Loading of RData Files

April 8, 2016
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Safe Loading of RData Files

Unless you have configured R not to ask, every time you close R or RStudio you are prompted to save your workspace. This saves an RData file to the working directory. The functions save.image() and save() offer a little more … Continue reading →

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R Markdown & Bloggin’: Part 1 – Inserting Code

April 8, 2016
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R Markdown & Bloggin’: Part 1 – Inserting Code

Reino Bruner April 8, 2016 As a data scientist, I find the vast majority of the useful content I produce just gets stored into a rainy day folder until I have further need for it. I think it would be more beneficial if I brought some of the functions, processes, and knowledge I have developed Continue Reading.. The post...

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Mapping Twitter Followers in R

April 8, 2016
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Mapping Twitter Followers in R

My colleague Jon Lieber and I recently released a new report that analyzes how digital marketplaces that connect workers to consumers demanding their services (e.g. Uber, Thumbtack, Upwork, etc.) are affecting the American labor market. As part of this report, we looked at where these digital marketplaces are most active. Although the biggest ones are now active...

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Election analysis contest entry part 3 – interactive exploration of voting locations with leaflet and Shiny

April 8, 2016
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Election analysis contest entry part 3 – interactive exploration of voting locations with leaflet and Shiny

Motivation This post is the third in a series that make up my entry in Ari Lamstein’s R Election Analysis Contest. First I introduced the nzelect R package from a user perspective. Second was a piece on how the build of that package works. Today, the third in the series introduces an interactive map of...

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Shiny module design patterns: Pass a single input to multiple modules

April 8, 2016
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Shiny module design patterns: Pass a single input to multiple modules

For the awesome Shiny Developers Conference back in January, I endeavoured to learn about shiny modules and overhaul an application using them in the space of two days. I succeeded and almost immediately switched onto other projects, thereby losing most of the hard-won knowledge! As I rediscover shiny modules and start putting them into more The post

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d3/R Chord Diagram of White House Petition Data

April 7, 2016
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d3/R Chord Diagram of White House Petition Data

The OpenData movement has the White House producing and releasing some novel datasets. One of them is the We The People petition site. I learned about this from Proofreader.com’s interesting python work using that data. From the petition site, you can see an interesting gallery of work done in different language and for different...

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How long could it take to run a regression

April 6, 2016
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How long could it take to run a regression

This afternoon, while I was discussing with Montserrat (aka @mguillen_estany) we were wondering how long it might take to run a regression model. More specifically, how long it might take if we use a Bayesian approach. My guess was that the time should probably be linear in , the number of observations. But I thought I would be good to check. Let...

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AirbnB uses R to scale data science

April 5, 2016
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AirbnB uses R to scale data science

Airbnb, the property-rental marketplace that helps you find a place to stay when you're travelling, uses R to scale data science. Airbnb is a famously data-driven company, and has recently gone through a period of rapid growth. To accommodate the influx of data scientists (80% of whom are proficient in R, and 64% use R as their primary data...

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