recogeo: A new R package to reconcile changing geographic boundaries (and corresponding variables)

Demographics information is usually reported in relation to precise boundaries: administrative, electoral, statistical, etc. Comparing demographics information reported at different point in time is often problematic because boundaries keep changing. The recogeo package faciliates reconciling boundaries and their data by a spatial analysis of the boundaries of two different periods. In this post, I explain how to install the package, reconcile two spatial objects and check the results.

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Friday, 1 February 2019

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RSS r-bloggers.com

  • 2 Months in 2 Minutes – rOpenSci News, June 2019
    rOpenSci HQ 👨🏽‍💻👩🏼‍💻 🏗️ Join our next Community Call on Involving Multilingual Communities June 28th. Video of our Community Call on Security for R is up, with a long list of resources. Our Community Manager, Stefanie Butland, spoke at R-Ladies Seattle and Fred Hutch about rOpenSci, Learning R, and Building Community May 22nd. Software Peer […]
  • Computation time of loops — for, *apply, map
    It is usually said, that for– and while-loops should be avoided in R. I was curious about just how the different alternatives compare in terms of speed. The first loop is perhaps the worst I can think of – the return vector is initialized without type and length so that the memory is constantly being […]
  • AzureVM update: flexible and powerful deployment and management of VMs in Azure
    by Hong Ooi, senior data scientist, Microsoft Azure I'm happy to announce version 2.0 of AzureVM, a package for deploying and managing virtual machines in Azure. This is a complete rewrite of the package, with the objective of making it a truly generic and flexible tool for working with VMs and VM scale sets (clusters). […]
  • Optimising your R code – a guided example
    Do you want to optimise your code but don't know where to start? In this post I guide you through my thought process when I optimised my code. Der Beitrag Optimising your R code – a guided example erschien zuerst auf STATWORX.
  • A Gentle Introduction to tidymodels
    Recently, I had the opportunity to showcase tidymodels in workshops and talks. Because of my vantage point as a user, I figured it would be valuable to share what I have learned so far. Let’s begin by framing where tidymodels fits in our analysis projects. The diagram above is based on the R for Data […]

RSS Simply Statistics

  • Research quality data and research quality databases
    When you are doing data science, you are doing research. You want to use data to answer a question, identify a new pattern, improve a current product, or come up with a new product. The common factor underlying each of these tasks is that you want to use the data to answer a question that […]
  • I co-founded a company! Meet Problem Forward Data Science
    I have some exciting news about something I’ve been working on for the last year or so. I started a company! It’s called Problem Forward data science. I’m pumped about this new startup for a lot of reasons. My co-founder is one of my families closest friends, Jamie McGovern, who has more than 2 decades […]
  • Generative and Analytical Models for Data Analysis
    Describing how a data analysis is created is a topic of keen interest to me and there are a few different ways to think about it. Two different ways of thinking about data analysis are what I call the “generative” approach and the “analytical” approach. Another, more informal, way that I like to think about […]

RSS Statistical Modeling, Causal Inference, and Social Science

  • “The writer who confesses that he is ‘not good at attention to detail’ is like a pianist who admits to being tone deaf”
    Edward Winter wrote: It is extraordinary how the unschooled manage to reduce complex issues to facile certainties. The writer who confesses that he is ‘not good at attention to detail’ (see page 17 of the November 1990 CHESS for that stark, though redundant, admission by the Weekend Wordspinner) is like a pianist who admits to […]
  • Harvard dude calls us “online trolls”
    Story here. Background here (“How post-hoc power calculation is like a shit sandwich”) and here (“Post-Hoc Power PubPeer Dumpster Fire”). OK, to be fair, “shit sandwich” could be considered kind of a trollish thing for me to have said. But the potty language in this context was not gratuitous; it furthered the larger point I […]
  • Random patterns in data yield random conclusions.
    Bert Gunter points to this New York Times article, “How Exercise May Make Us Healthier: People who exercise have different proteins moving through their bloodstreams than those who are generally sedentary,” writing that it is “hyping a Journal of Applied Physiology paper that is now my personal record holder for most extensive conclusions from practically […]