Monthly Archives: March 2018

Startup with Secrets – A Poor Man’s Approach

March 29, 2018
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Startup with Secrets – A Poor Man’s Approach

New release: startup 0.10.0 is now on CRAN. If your R startup files (.Renviron and .Rprofile) get long and windy, or if you want to make parts of them public and other parts private, then you can use the startup package to split them up in separate files and directories under .Renviron.d/ and .Rprofile.d/. For instance, the .Rprofile.d/repos.R file...

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Who is coming to eRum 2018 in Budapest?

Who is coming to eRum 2018 in Budapest?

Discover who is coming to eRum 2018 in Budapest while playing with an interactive data visualization in D3.js. Vist visualization’s page. You can meet me (Olga) at the conference where I’ll be speaking about cool and open source packages ...

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Lintr Bot, lintr’s Hester egg

March 29, 2018
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Lintr Bot, lintr’s Hester egg

Remember my blog post about automatic tools for improving R packages? One of these tools is Jim Hester’s lintr, a package that performs static code analysis. In my experience it mostly helps identifying too long code lines and missing space, although...

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BotRNot: An R app to detect Twitter bots

March 29, 2018
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BotRNot: An R app to detect Twitter bots

Twitter's bot problem is well documented, influencing discourse on divisive topics like politics and civil rights. But it's getting harder and harder to spot such nefarious bots, who often borrow biographies and tweets from real (and often stolen) profiles to evade detection. (The New York Times recently published an outstanding feature on bots and follower factories.) Can we distinguish...

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Version 0.6-10 of NIMBLE released

March 29, 2018
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Version 0.6-10 of NIMBLE released

We’ve released the newest version of NIMBLE on CRAN and on our website. Version 0.6-10 primarily contains updates to the NIMBLE internals that may speed up building and compilation of models and algorithms, as well as a few bug fixes. Changes include: some steps of model and algorithm building and compilation are faster; compiled execution

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Hangul/Korean edition of Practical Data Science with R!

March 29, 2018
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Hangul/Korean edition of Practical Data Science with R!

Excited to see our new Hangul/Korean edition of “Practical Data Science with R” by Nina Zumel, John Mount, translated by Daekyoung Lim. Thank you for producing a handsome edition, Manning and JPub.kr!

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How to map public debt data with ggplot2

March 29, 2018
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How to map public debt data with ggplot2

You’ve heard me say it a thousand times: to master data science, you need to practice. You need to “practice small” by practicing individual techniques and functions. But you also need to “practice big” by working on larger projects. To get some practice, my recommendation is to find reasonably sized datasets online and plot them. The post How to...

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How to map public debt data with ggplot2

March 29, 2018
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How to map public debt data with ggplot2

You’ve heard me say it a thousand times: to master data science, you need to practice. You need to “practice small” by practicing individual techniques and functions. But you also need to “practice big” by working on larger projects. To get some practice, my recommendation is to find reasonably sized datasets online and plot them. The post How to...

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R⁶ — Capturing [YouTube] Captions

March 29, 2018
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(R⁶ == brief, low-expository posts) @yoniceedee suggested I look at the Cambridge Analytics “whistleblower” testimony proceedings: @hrbrmstr giving the term "improving r&d" a whole new meaning … https://t.co/f1KA8U3htT — yoni sidi (@yoniceedee) March 29, 2018 I value the resources @yoniceedee tosses my way (they often end me down twisted paths like this one, though :-)... Continue reading →

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pandas vs. data.table – A study of data-frames – Part 2

March 29, 2018
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pandas vs. data.table – A study of data-frames – Part 2

The story continues As Christian and I have already mentioned in part 1 of this simulation study series, pandas and data.table have become the most widely used packages for data manipulation in Python and R, respectively (in R, of course, one may not miss mentioning the dplyr package). Furthermore, at STATWORX we have experts in both domains, and besides...

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