r | Thought splinters

Introduction to R for Social Scientists (I2RSS)

Sat, 02 Apr 2022 00:00:00 +0000

Acclamations for I2RSS

From my training (Ph.D. in sociology) but also from my different professorship on educational sciences, I was pleased finally to see a new R introduction especially directed at social scientists. The book title “Introduction to R for Social Scientists: A Tidy Programming Approach” (abbreviated I2RSS) was promising for me for two reasons.

The book is written by Ryan Kennedy and Philip Waggoner, two prestigious scientists involved in political and social research. Whereas Ryan has an astonishing career in political science, is Philip exceptionally experienced at an academic level in computational social science and data science. Philip is also a member of easystats (a software group that tends to an ecosystem of packages making statistics in R easy).

Promoting the modern tidyverse approach

The book features the tidyverse approach a modern collection of R packages that share an underlying design philosophy, grammar, and data structures.

Real data, results discussed and gentle dialog with reader

Without doubts, the book has several other merits: It uses real data sets, e.g., from the American National Election Studies (ANES) and teaches data management, visualizations, exploratory data analysis (EDA), and statistical modeling not in an abstract way, but also discusses the exciting results with their data sets. It talks to the reader in a very sympathetic and comforting way to master the (still very) steep learning curve for R beginners.

Some drawbacks and failures

But unfortunately, there are also two significant drawbacks to this introduction:

Educational inconsistencies

The book has several weaknesses from an educational point of view:

With some exceptions (data classes, data structures, and the map function from the purrr package is the chapter on “Essential programming,” in my personal view to advanced for R beginners, especially for people from the social sciences with no programming background.
Comparing the same results with base R and tidyverse code may be interesting for intermediate users. Still, it is a waste of time and complicates things for beginners. It is also misusing the sparse place in the book, which has only 198 pages.
The book uses R scripts and does not feature Rmd files. This is strange as literary programming is an essential step for reproducibility, and RMarkdown also facilitates interactive use of the program code.
Sometimes, the results of the code chunks are missings (e.g., graphs, tables, or reports). The explaining text under the code is, therefore, abstract. There are also some link errors, providing an URL starting with “www” where the referring webpage does not need/accept this addition.

These above weaknesses result in the deduction of one of the five stars.

Not a role model for Open Science

The second star deduction is motivated by missing teaching modern scientific behavior for early career researchers (ECRs). This shortcoming includes the prominent use of R Markdown and the use of collaboration and Open Science. I think that after the publication of Happy Git, there is no excuse anymore to teach Git and GitHub (or similar systems) even for R beginners. Another big mistake is not using the open-access politics of the bookdown.org infrastructure for the online version of the book.

In the book, the authors promote the friendliness and importance of the R community several times. They even mention that the book was initially written with the help of the bookdown package (page 2). So why not supply a role model for R beginners and young researchers?

Announcing the R package coinsR

Fri, 02 Aug 2019 00:00:00 +0000

Update 2021-05-21: Because of some breaking changes in the Hugo site structure and management in the last three years, coinsR works at the moment only with individual pages.

This blog entry announces the R program coinsR to produce bibliographic metadata automatically for websites within the Hugo framework. The dominant use case at the moment is with the blogdown package.

In a previous blog entry I wrote about the advantages of providing bibliographic metadata for your web pages producing COinS. COinS is the abbreviation of Context Objects in Spans. It refers to a microformat standard to embed bibliographic metadata as HTML.

A COinS string includes HTML code for all the information necessary to cite a publication correctly. It works for every type of writing (books, papers, web pages). COinS embedded in your HTML pages help your blog readers or website visitors to cite your posts and pages correctly.

I wrote also a detailed tuorial how to produce COinS with the help of the free bibliographical research tool Zotero. But this is a quite complicated procedure with several steps. Besides, it works only for every page individually and not automatically for all blog entries of your website.

To produce COinS for every web page quickly was my motivation to write the R package coinsR.

Use cases of `coinsR` and its limitations

The package requires:

Hugo with the R package blogdown
Config file in the TOML format (config.toml)
Blog entries with YAML frontmatter

I plan for a future version to loosen the last two limitations and allow config.yaml and TOML frontmatter (but not for .json).

Update 2021-05-21: This plan is still relevant: I would like to loosen some restrictions and improve the user interface.

You can call coinsR via an RStudio Addin for every page individually. But you can also produce COinS automatically for all files under a specific directory.

Where to find `coinsR` and how to install it?

You can download the package from Github with

remotes::install_github('petzi53/coinsR', build_vignettes = TRUE)

I am trying to prepare coinsR as an R package distributed via the CRAN repository. But as I am still not very experienced in R programming, I am not sure if I will succeed.

You will find a detailed description in the help file and the vignette description of how to invoke the two functions coins_this() and coins_all().

R installieren (Deutsch)

Tue, 02 Jan 2018 00:00:00 +0000

R installieren

Bedienung dieser Präsentation

Steuerungselemente: Pfeile rechts unten
Achtung: Manchmal gibt es außer vor und zurück auch hinauf und hinunter
Folienstruktur-Überblick: ESC-Taste
Beenden: Mit dem Browser zurück gehen

Voraussetzungen

Bevor wir komfortabel mit R arbeiten können, müssen wir einige Programme installieren

Die aktuelle Version von R
Die aktuelle Version der Entwicklungsumgebung RStudio
Die aktuelle Version von LaTeX

Alle Programme sind Open Source: Sowohl Quellcode als auch Programme sind frei und kostenlos erhältlich.

Neuinstallation von R

Wir beginnen mit der Neu-Installation von R
Und zwar für Mac OS und für Windows

ACHTUNG: Wenn Sie bereits (eine ältere Version von) R installiert haben, dann folgen Sie statt dessen for Windows dieser Anleitung and for Mac dieser Anleitung.

Die R-Startseite

CRAN aufrufen

Wählen Sie Ihre R-Version aus

Mac: Klicken Sie auf Download-Seite für Mac OS X
Windows: gehen Sie zur nächsten Folie (Pfeil rechts)
Weiter für Mac: Pfeil nach unten wählen

1a R-Installation für MacOS X

Klicken Sie auf die neueste R-Version
(hier R-3.4.3.pkg: Stand Januar 2018)

1b Datei .pkg speichern

Es öffnet sich nun ein Fenster
Wählen Sie einen Speicherort
Sichern Sie die Datei

1c R installieren

Öffnen Sie im Betriebssystem die gespeicherte Datei
Es öffnet sich das Installationsprogramm
Befolgen Sie die Anweisungen (“Fortfahren”)

Rufen Sie R auf

Rufen Sie die R.app auf
Geben Sie 2 +2 als Test ein:

Vergleichen Sie Ihr Ergebnis

Beenden Sie Ihre Eingabe mit return
Erscheint [1] 4?
Dann haben Sie R erfolgreich installiert!

Präsentation beenden

Es kann sein, dass der Text Ihrer R-Version leicht unterschiedlich ist. So kann er z.B. komplett in Deutsch geschrieben sein.

Sie beenden nun diese Präsentation mit (Browser Pfeil rückwärts)
ACHTUNG: Browser rückwärts – und nicht Folien Pfeil links!

2. Installiere R für Windows

Gehen Sie auf die Download-Seite für Windows

Download der aktuellen R-Version

R Download für Windows

Windows-Bilschirmfotos gesucht

Ich habe leider keine weiteren Screenshots.

Installieren Sie gerade R für Windows?

Dann schicken Sie mir bitte Screenshots.

Ich baue sie dann in diese Präsentation ein!

Präsentation beenden

Sie beenden nun diese Präsentation mit (Browser Pfeil rückwärts)
ACHTUNG: Browser rückwärts – und nicht Folien Pfeil links!

r | Thought splinters

Introduction to R for Social Scientists (I2RSS)

Acclamations for I2RSS

Authors experienced in political, social & dats science

Promoting the modern tidyverse approach

Real data, results discussed and gentle dialog with reader

Some drawbacks and failures

Educational inconsistencies

Not a role model for Open Science

Announcing the R package coinsR

Use cases of coinsR and its limitations

Where to find coinsR and how to install it?

R installieren (Deutsch)

R installieren

Voraussetzungen

Neuinstallation von R

CRAN aufrufen

Wählen Sie Ihre R-Version aus

1a R-Installation für MacOS X

1b Datei .pkg speichern

1c R installieren

Rufen Sie R auf

Vergleichen Sie Ihr Ergebnis

Präsentation beenden

2. Installiere R für Windows

Download der aktuellen R-Version

Windows-Bilschirmfotos gesucht

Präsentation beenden

Use cases of `coinsR` and its limitations

Where to find `coinsR` and how to install it?