A new version of pander was just released on CRAN with 200+ commits of new features, major performance updates and some minor fixes . One of the minor technical changes, which might be major good news for the knitr users, is that there is no further need to specify asis in knitr chunks when calling pander – please...
Or how to create a world map in R with survey data, World Bank indicators, ggplot2 and rworldmap by timwinke When people think about Germany, what comes to their mind? Oktoberfest, ok – but Mercedes might be second or BMW … Continue reading →
Dear Readers of The Chemical Statistician, While working in my job at the British Columbia Cancer Agency, I learned about a wonderful new data visualization resource from a colleague who works at the British Columbia Centre for Disease Control. I want to share this with you, as I think that it will help you immensely in your efforts
I really like National Geographic. Their magazine is great, their television documentaries are done well and they helped give me a lifelong love of maps. They generate very good information and help shed light on the world we all share. So why is this graphic so awful? Let's have a look: We'll start off by
An invisible red thread connects those destined to meet, regardless of time, place or circumstances. The thread may stretch or tangle, but never break (Ancient Chinese Legend) I use to play once a year with my friends to Secret Santa (in Spain we call it Amigo Invisible). As you can read in Wikipedia: Secret Santa is
After having broken the Bayesian eggs and prepared your model in your statistical kitchen the main dish is the posterior. The posterior is the posterior is the posterior, given the model and the data it contains all the information you need and anything else will be a little bit less nourishing. However, taking in the posterior in one gulp...
Several months ago, I found Bryan Povlinkski's (really nicely cleaned) dataset with 2013 NFL play-by-play information, based on data released by Brian Burke at Advanced Football Analytics. I decided to browse QB completion rates based on Pass Location (Left, Middle, Right), Pass Distance (Short or Deep), and Down....
In the past week, colleagues of mine and me started using the lme4-package to compute multi level models. This inspired me doing two new functions for visualizing random effects (as retrieved by ranef()) and fixed effects (as retrieved by fixed()) of (generalized) linear mixed effect models. The upcoming version of my sjPlot package will contain
The jsonlite package implements a robust, high performance JSON parser and generator for R, optimized for statistical data and the web. This week version 0.9.13 appeared on CRAN which is the third release in a relatively short period focusing on performance optimization.
Fast number formatting
Version 0.9.11 and 0.9.12 had already introduced majors...
Days ago a study says that Santiago, city where I live, has one of the best
public transport system in LATAM (WAT?! define best please!). So I've search
for some information and I found
Anyway I tried to find some related data/gtfs/information to work/play and I found the
Transantiago GTFS. GTFS means General Transit Feed Specification and is a format for