Summary This post is about the surprising uses I’ve noticed and the questionsabout the censo2017 R package, a tool foraccessing the Chilean census 2017 data, I’ve gotten since it was peer-reviewedthrough rOpenSci one year ago. The originalpost about thepackage one year ago didn’t cover the different examples I present here,including a Python port of the R package.

Summary censo2017 is an R package designed toorganize the Redatam ¹ filesprovided by the Chilean National Bureau of Statistics (Instituto Nacional deEstadísticas de Chile in spanish) in DVD format ² . This package was inspiredby citesdb(Noam Ross, 2020) and taxadb(Carl Boettiger et al, 2021).This post is about thispackage, the problem it solves, how to use it, and the fact that the package andits review process were all

Dealing with taxonomic inconsistencies within and across datasets is a fundamental challenge of ecology and evolutionary biology. Accounting for species synonyms, taxa splitting and unification is especially important as aggregation of data across time and different data sources becomes increasingly common.

There seem to be a lot of ways to write about your R package, and rather than haveto decide on what to focus on I thought I’d write a little bit about everything.To begin with I thought it best to describe what problem rdhs tries to solve,why it was developed and how I came to be involved in this project.

Every R package has its story. Some packages are written by experts, some bynovices. Some are developed quickly, others were long in the making. This is thestory of jstor, a package which I developed during my time as a student ofsociology, working in a research project on the scientific elite withinsociology.

Introduction I never thought that I’d be programming software in my career. I startedusing R a little over 2 years now and it’s been one of the most importantdecisions in my career. Secluded in a small academic office with no oneto discuss/interact about my new hobby, I started searching the web fortutorials and packages. After getting to know how amazing and nurturingthe R community is, it made me want to become a data scientist.