Aim Create a dummy database Test dbplyr’s SQL translation Modify dbplyr’s SQL translation Testing the dbplyr hack Concluding notes At the end of my first post on CKAN discussing how to use the CKAN API to extract data from the NHS open data platform directly into R, I talked about how it would be neat to write some wrapper functions to make this process a...
Lately I’ve found myself using Jim Hester’s glue package instead of paste0 or sprintf. This post marks the start of an ongoing series of little magic spells using the glue package. The back story I’ve been through a few stages of discovery for combining strings of text together. First, it was just the very idea that this was possible - was AMAZING. paste When...
Aim Create a dummy database Test dbplyr’s SQL translation Modify dbplyr’s SQL translation Testing the dbplyr hack Concluding notes At the end of my first post on CKAN discussing how to use the CKAN API to extract data from the NHS open data platform directly into R, I talked about how it would be neat to write some wrapper functions to make this process a...
Normally when we visualize monthly precipitation anomalies, we simply use a bar graph indicating negative and positive values with red and blue. However, it does not explain the general context of these anomalies. For example, what was the highest or lowest anomaly in each month? In principle, we could use a boxplot to visualize the distribution of the anomalies,...
Unfortunately, I haven’t had as much time to make blog posts in the past year or so. I started taking classes as part of Georgia Tech’s Online Master of Science in Analytics (OMSA) program last summer (2018) while continuing to work full-time, so extra time to code and write hasn’t been abundant for me. Anyways, I figured I would share one neat thing I learned as...
In my last post I scraped some character statistics from the mobile game Star Wars: Galaxy of Heroes. In this post, I’ll be aiming to try out k-means clustering in order to see if it comes out with an intuitive result, and to learn how to integrate this kind of analysis into a tidy workflow using broom. First I’ll load...
I’ve released a version of my pqR implementation of R that has extensions for automatic differentiation. This is not a stable release, but it can be downloaded from pqR-project.org — look for the test version at the bottom — and installed the same as other pqR versions (from source, so you’ll need C and Fortran compilers).
Here is simple modeling problem in R. We want to fit a linear model where the names of the data columns carrying the outcome to predict (y), the explanatory variables (x1, x2), and per-example row weights (wt) are given to us as strings. Lets start with our example data and parameters. The point is: we … Continue reading Programming...
For a lonely soul, you’re having such a nice time (Nothing in my way, Keane) In my previous post, I created the P2 Penrose tessellation according to the instructions of this post. Now it’s time to create the P3 tessellation following the same technique I described already. This is the image of the P3 tessellation: … Continue reading Rhombuses...
I recently had a question from a colleague, and thanks to the awesome recent work on rlang this is now super straightforward. I thought I’d share a bit about that. I still remember when I had just learnt how to write a function in R, and I wanted to do the thing where you use a function argument that isn’t...
Most Wednesday’s I enjoy reading The Knowledge blog on the Guardian’s website and reading the football trivia therein. When time (and questions) allow, I like to answer some of the questions posed, example of which are here, here, and here. League of Nations The first question comes from Which player had the nationality with the lowest FIFA World Ranking at the time...
For a recent blogpost, I required data on the ELO ratings of national football teams over time. Such a list exists online at eloratings.net and so in theory this was just a simple task for rvest to read the html pages on that site and then fish out the data I wanted. However, while this works for the static...
I’ve been an R user for a few years now and the data.table package has been my staple package for most of it. In this post I wanted to talk about why almost every script and RMarkdown report I write start with: library(data.table) My memory issues I started working on my licenciate thesis (the argentinian equivalent to a Masters Degree) around mid...
Organic Development of R Artefacts In a previous post, I alluded to the point that one of the great strengths (but also one of the challenges) of R is the organic way in which R ‘artefacts’ are developed.1 One characteristic of this “organic d...
Are you interested in guest posting? Publish at DataScience+ via your editor (i.e., RStudio). Category Basic Statistics Tags Linear Regression R Programming Tips & Tricks Integration is the process of evaluating integrals. It is one of the two central ideas of calculus and is the inverse of the other central idea of calculus, differentiation. Generally, we can speak of integration in two different contexts: the...
With Alfred Galichon and Lucas Vernet, we recently uploaded a paper entitled optimal transport on large networks on arxiv. This article presents a set of tools for the modeling of a spatial allocation problem in a large geographic market and gives examples of applications. In our settings, the market is described by a network that maps the cost of...
Motivation There are several wonderful tools for retrieving information about R packages, some of which are listed below: cranlogs, dlstats and packageRank for R package download stats pkgsearch and packagefinder for searching CRAN R packages crandb provides API for programatically accessing meta-data cchecks for CRAN check results We have used some or all of these to track/monitor our own R packages available on CRAN. Over...
This morning swephR version 0.2.0 made it unto CRAN and is now propagating to the mirrors. The goal of swephR is to provide an R interface to the Swiss Ephemeris, a high precision ephemeris based upon the DE431 ephemeris from NASA’s JPL. It covers the time range 13201 BCE to 17191 CE. The new version 0.2.0 brings two important changes. First, the version of the included Swiss...
As the monsoon rains fall, another TokyoR User Meetup! On June 29th, useRs from all over Tokyo flocked to Hanzomon, Tokyo for another jam-packed session of #rstats hosted by Infocom. In line with my previous round up posts: ...
A few days ago, I released a new version of my R package, groupdata2, on CRAN. groupdata2 contains a set of functions for grouping data, such as creating balanced partitions… Read More → Indlægget groupdata2 version 1.1.0 released on CRAN blev først udgivet på .
This morning, digest version 0.6.20 went to CRAN, and I will send a package to Debian shortly as well. digest creates hash digests of arbitrary R objects (using the md5, sha-1, sha-256, sha-512, crc32, xxhash32, xxhash64, murmur32, and spookyhash algorithms) permitting easy comparison of R language objects. This version contains only internal changes with a switch to the (excellent) tinytest package....
After a fairly long life on GitHub, my R package, cvms, for cross-validating linear and logistic regression, is finally on CRAN! With a few additions in the past months, this… Read More → Indlægget cvms 0.1.0 released on CRAN blev først udgivet på .
Curious to know how did our last MilanoR Meeting end up? Check out some photos, resources and the highlights of the night. The post 10th MilanoR meeting: photos and resources appeared first on MilanoR.
As part of the development of a Shiny application for production using {golem}, we recommend, among other things, working with Shiny-modules. The communication of data between the different modules can be complex. At ThinkR we use a strategy: the stratégie du petit r. We explain everything in this article. What is a module? A module is the combination of...
We are happy to announce the R package compareWith, providing user-friendly RStudio addins that simplify diff and merge tasks. Just ahead of the upcoming useR!2019 Toulouse, where Miraier Nikki will be introducing the package in a short talk during ...
Motivation I’ve written before about my learning plans, which always seem to be in a state of flux, and in particular learning about machine learning. Part of the reason why I’m so reticent is because I’m a mathematician and statistics does not come natural or easy for me. My limited past experience has exposed to me just how much I don’t...
For a few of my commercial projects I have been in the seemingly strange place being asked to port a linear model from one data science system to another. Now I try to emphasize that it is better going forward to port procedures and build new models with training data. But sometimes that is not … Continue reading Replicating...
Remember Magic Eye pictures? It was a craze in the 1990s where you would get books of abstract Pollockesque images, and, using a special technique, you could see a “3D” image. The technique, which I could never properly master, was to see “through” the page, focusing your gaze on a point behind the paper. The
I stumbled upon a nice little puzzle in Gloucestershire, England: Arrange the numbers 1 to 16, so each two numbers next to each other, add up to a square number. (You can only use each number once). Devastatingly succinct. But potentially tricky. I reached out, as I always do, to R to help narrow the
Jobs for R users