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A tutorial on tidy cross-validation with R Analyzing NetHack data, part 1: What kills the players Analyzing NetHack data, part 2: What players kill the most Building a shiny app to explore historical newspapers: a step-by-step guide Classification of historical newspapers content: a tutorial combining R, bash and Vowpal Wabbit, part 1 Classification of historical newspapers content: a tutorial combining R, bash and Vowpal Wabbit, part 2 Curly-Curly, the successor of Bang-Bang Dealing with heteroskedasticity; regression with robust standard errors using R Easy time-series prediction with R: a tutorial with air traffic data from Lux Airport Exporting editable plots from R to Powerpoint: making ggplot2 purrr with officer Fast food, causality and R packages, part 1 Fast food, causality and R packages, part 2 For posterity: install {xml2} on GNU/Linux distros Forecasting my weight with R From webscraping data to releasing it as an R package to share with the world: a full tutorial with data from NetHack Get text from pdfs or images using OCR: a tutorial with {tesseract} and {magick} Getting data from pdfs using the pdftools package Getting the data from the Luxembourguish elections out of Excel Going from a human readable Excel file to a machine-readable csv with {tidyxl} Historical newspaper scraping with {tesseract} and R How Luxembourguish residents spend their time: a small {flexdashboard} demo using the Time use survey data Imputing missing values in parallel using {furrr} Intermittent demand, Croston and Die Hard Looking into 19th century ads from a Luxembourguish newspaper with R Making sense of the METS and ALTO XML standards Manipulate dates easily with {lubridate} Manipulating strings with the {stringr} package Maps with pie charts on top of each administrative division: an example with Luxembourg's elections data Missing data imputation and instrumental variables regression: the tidy approach Modern R with the tidyverse is available on Leanpub Objects types and some useful R functions for beginners Pivoting data frames just got easier thanks to `pivot_wide()` and `pivot_long()` R or Python? Why not both? Using Anaconda Python within R with {reticulate} Searching for the optimal hyper-parameters of an ARIMA model in parallel: the tidy gridsearch approach Some fun with {gganimate} Split-apply-combine for Maximum Likelihood Estimation of a linear model Statistical matching, or when one single data source is not enough The best way to visit Luxembourguish castles is doing data science + combinatorial optimization The never-ending editor war (?) The year of the GNU+Linux desktop is upon us: using user ratings of Steam Play compatibility to play around with regex and the tidyverse Using Data Science to read 10 years of Luxembourguish newspapers from the 19th century Using a genetic algorithm for the hyperparameter optimization of a SARIMA model Using cosine similarity to find matching documents: a tutorial using Seneca's letters to his friend Lucilius Using linear models with binary dependent variables, a simulation study Using the tidyverse for more than data manipulation: estimating pi with Monte Carlo methods What hyper-parameters are, and what to do with them; an illustration with ridge regression {disk.frame} is epic {pmice}, an experimental package for missing data imputation in parallel using {mice} and {furrr} Building formulae Functional peace of mind Get basic summary statistics for all the variables in a data frame Getting {sparklyr}, {h2o}, {rsparkling} to work together and some fun with bash Importing 30GB of data into R with sparklyr Introducing brotools It's lists all the way down It's lists all the way down, part 2: We need to go deeper Keep trying that api call with purrr::possibly() Lesser known dplyr 0.7* tricks Lesser known dplyr tricks Lesser known purrr tricks Make ggplot2 purrr Mapping a list of functions to a list of datasets with a list of columns as arguments Predicting job search by training a random forest on an unbalanced dataset Teaching the tidyverse to beginners Why I find tidyeval useful tidyr::spread() and dplyr::rename_at() in action Easy peasy STATA-like marginal effects with R Functional programming and unit testing for data munging with R available on Leanpub How to use jailbreakr My free book has a cover! Work on lists of datasets instead of individual datasets by using functional programming Method of Simulated Moments with R New website! Nonlinear Gmm with R - Example with a logistic regression Simulated Maximum Likelihood with R Bootstrapping standard errors for difference-in-differences estimation with R Careful with tryCatch Data frame columns as arguments to dplyr functions Export R output to a file I've started writing a 'book': Functional programming and unit testing for data munging with R Introduction to programming econometrics with R Merge a list of datasets together Object Oriented Programming with R: An example with a Cournot duopoly R, R with Atlas, R with OpenBLAS and Revolution R Open: which is fastest? Read a lot of datasets at once with R Unit testing with R Update to Introduction to programming econometrics with R Using R as a Computer Algebra System with Ryacas

For posterity: install {xml2} on GNU/Linux distros

Today I’ve removed my system’s R package and installed MRO instead. While re-installing all packages, I’ve encountered one of the most frustrating error message for someone installing packages from source:

Error : /tmp/Rtmpw60aCp/R.INSTALL7819efef27e/xml2/man/read_xml.Rd:47: unable to load shared object
libicui18n.so.58: cannot open shared object file: No such file or directory ERROR: 
installing Rd objects failed for package ‘xml2’ 

This library, libicui18n.so.58 is a pain in the butt. However, you can easily install it if you install miniconda. After installing miniconda, you can look for it with:

[19-05-18 18:26] cbrunos in ~/ ➤ locate libicui18n.so.58


So now you need to tell R where to look for this library. The following Stackoverflow answer saved the day. Add the following lines to R_HOME/etc/ldpaths (in my case, it was in /opt/microsoft/ropen/3.5.2/lib64/R/etc/):


and try to install xml2 again, and it should work! If not, just abandon the idea of using R and switch to doing data science with VBA, it’ll be less frustrating.

Something else, if you install Microsoft R Open, you’ll be stuck with some older packages, because by default MRO uses a snapshot of CRAN from a given day as a mirror. To get the freshest packages, add the following line to your .Rprofile file (which should be located in your HOME):

options(repos = c(CRAN = "http://cran.rstudio.com/"))

And to finish this short blog post, add the following line to your .Rprofile if you get the following error messages when trying to install a package from github:

remotes::install_github('rstudio/DT') Downloading GitHub repo rstudio/DT@master tar: 
This does not look like a tar archive gzip: stdin: unexpected end of file tar: Child returned 
status 1 tar: Error is not recoverable: exiting now tar: This does not look like a tar archive 
gzip: stdin: unexpected end of file tar: Child returned status 1 tar: Error is not recoverable: 
exiting now Error in getrootdir(untar(src, list = TRUE)) : length(file_list) > 0 is not TRUE Calls: 
<Anonymous> ... source_pkg -> decompress -> getrootdir -> stopifnot In addition: Warning messages: 1: 
In utils::untar(tarfile, ...) : ‘tar -xf '/tmp/RtmpitCFRe/file2677442609b8.tar.gz' -C 
'/tmp/RtmpitCFRe/remotes267752f2629f'’ returned error code 2 2: 
In system(cmd, intern = TRUE) : running command 'tar -tf '/tmp/RtmpitCFRe/file2677442609b8.tar.gz'' 
had status 2 Execution halted

The solution, which can found here

options("download.file.method" = "libcurl")

Hope you enjoyed! If you found this blog post useful, you might want to follow me on twitter for blog post updates and buy me an espresso or paypal.me.

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