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Exporting editable plots from R to Excel: making ggplot2 purrr with officer

Exporting editable plots from R to Excel: making ggplot2 purrr with officer

I was recently confronted to the following problem: creating hundreds of plots that could still be edited by our client. What this meant was that I needed to export the graphs in Excel or Powerpoint or some other such tool that was familiar to the client, and not export the plots directly to pdf or png as I would normally do. I...

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How Luxembourguish residents spend their time: a small {flexdashboard} demo using the Time use survey data

September 13, 2018
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How Luxembourguish residents spend their time: a small {flexdashboard} demo using the Time use survey data

In a previous blog post I have showed how you could use the {tidyxl} package to go from a human readable Excel Workbook to a tidy data set (or flat file, as they are also called). Some people then contributed their solutions, which is always something I really enjoy when it happens. This way, I also get to learn things! @expersso proposed a...

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Going from a human readable Excel file to a machine-readable csv with {tidyxl}

September 10, 2018
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Going from a human readable Excel file to a machine-readable csv with {tidyxl}

I won’t write a very long introduction; we all know that Excel is ubiquitous in business, and that it has a lot of very nice features, especially for business practitioners that do not know any programming. However, when people use Excel for purposes it was not designed for, it can be a hassle. Often, people use Excel as a reporting tool, which...

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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

September 7, 2018
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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

I’ve been using GNU+Linux distros for about 10 years now, and have settled for openSUSE as my main operating system around 3 years ago, perhaps even more. If you’re a gamer, you might have heard about SteamOS and how more and more games are available on GNU+Linux. I don’t really care about games, I play the occasional one (currently Tangledeep) when...

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Dealing with heteroskedasticity; regression with robust standard errors using R

Dealing with heteroskedasticity; regression with robust standard errors using R

First of all, is it heteroskedasticity or heteroscedasticity? According to McCulloch (1985), heteroskedasticity is the proper spelling, because when transliterating Greek words, scientists use the Latin letter k in place of the Greek letter κ (kappa). κ sometimes is transliterated as the Latin letter c, but only when these words entered the English language through French, such as scepter. Now that this is out of...

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Missing data imputation and instrumental variables regression: the tidy approach

Missing data imputation and instrumental variables regression: the tidy approach

In this blog post I will discuss missing data imputation and instrumental variables regression. This is based on a short presentation I will give at my job. You can find the data used here on this website: http://eclr.humanities.manchester.ac.uk/index.php/IV_in_R The data is used is from Wooldridge’s book, Econometrics: A modern Approach. You can download the data by clicking here. This is the variable description: 1....

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Forecasting my weight with R

Forecasting my weight with R

I’ve been measuring my weight almost daily for almost 2 years now; I actually started earlier, but not as consistently. The goal of this blog post is to get re-acquaiented with time series; I haven’t had the opportunity to work with time series for a long time now and I have seen that quite a few packages that deal with time series...

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Getting data from pdfs using the pdftools package

Getting data from pdfs using the pdftools package

It is often the case that data is trapped inside pdfs, but thankfully there are ways to extract it from the pdfs. A very nice package for this task is pdftools (Github link) and this blog post will describe some basic functionality from that package. First, let’s find some pdfs that contain interesting data. For this post, I’m using the diabetes country profiles from...

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{pmice}, an experimental package for missing data imputation in parallel using {mice} and {furrr}

Yesterday I wrote this blog post which showed how one could use {furrr} and {mice} to impute missing data in parallel, thus speeding up the process tremendously. To make using this snippet of code easier, I quickly cobbled together an experimental package called {pmice} that you can install from Github: devtools::install_github("b-rodrigues/pmice") For now, it returns a list of mids objects and not a...

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Imputing missing values in parallel using {furrr}

Today I saw this tweet on my timeline: For those of us that just can't wait until RStudio officially supports parallel purrr in #rstats, boy have I got something for you. Introducing `furrr`, parallel purrr through the use of futures. Go ahead, break things, you know you want to:https://t.co/l9z1UC2Tew— Davis Vaughan (@dvaughan32) April 13, 2018 and as a heavy {purrr} user,...

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