SatRday Paris 2019 Slides on Futures

March 7, 2019
By
SatRday Paris 2019 Slides on Futures

Below are links to my slides from my talk on Future: Friendly Parallel Processing in R for Everyone that I presented last month at the satRday Paris 2019 conference in Paris, France (February 23, 2019). My talk (32 slides; ~40 minutes): Title: F...

Read more »

gower 0.2.0 is on CRAN

March 7, 2019
By
gower 0.2.0 is on CRAN

A new version of R package gower has just been released on CRAN. Thanks to our new contributor David Turner who was kind enough to provide a pull request, gower now also computes weighted gower distances. From the NEWS file: … Continue reading →

Read more »

Shiny vs. Dash: A Side-by-side comparison

March 6, 2019
By
Shiny vs. Dash: A Side-by-side comparison

A side-by-bide comparison of R’s Shiny and Python’s Dash for building a simple web app. We’ll also discuss some of the unseen differences between the two that are important to consider before building a large scale app and deploying it.

Read more »

How to eyeball a standard deviation

March 6, 2019
By
How to eyeball a standard deviation

TEST YOUR ESTIMATION SKILLS Click to enlarge Suppose you are looking at the roughly normally distributed data above and you want to visually estimate the standard deviation. What would you guess? 20? 35? How would you do it? In a past post we talked about tips for drawing a normal distribution. In it, we noted The post How to...

Read more »

Forecasting From a Regression with a Square Root Dependent Variable

March 6, 2019
By
Forecasting From  a Regression with a Square Root Dependent Variable

Back in 2013 I wrote a post that was titled, "Forecasting From Log-Linear Regressions". The basis for that post was the well-known result that if you estimate a linear regression model with the (natural) logarithm of y as the dependent variable, but you're actually interested in forecasting y itself, you don't just report the exponentials of the original forecasts. You...

Read more »

The Global Carbon Footprint (1970 – 2015)

March 6, 2019
By
The Global Carbon Footprint (1970 – 2015)

This project is an interactive and dynamic visualization tool that displays global Carbon emissions data over the years (from 1970 till 2015). It is hosted on a Shiny application that was developed in RStudio. Please check out the app here & the code behind the project can be viewed here.   Project Motivation Even though the history of climate change science reaches further...

Read more »

RInside 0.2.15

March 6, 2019
By

A new release 0.2.15 of RInside arrived on CRAN and in Debian today. This marks the first release in almost two years, and it brings some build enhancements. RInside provides a set of convenience classes which facilitate embedding of R inside of C++ applications and programs, using the classes and functions provided by Rcpp. RInside is stressing the CRAN system...

Read more »

R Vocabulary – Part 4

March 6, 2019
By
R Vocabulary – Part 4

This is the fourth and final part in the series of articles on R vocabulary. In this series, we explore most of the functions mentioned in Chapter 2 of the book Advanced R. The first, second and third part of the series can be read here, here and here. In this article, we explore most of the functions mentioned under...

Read more »

MODIStsp v. 1.3.8 is out !

A new version of MODIStsp (1.3.8) is on CRAN as of today ! The new version fixes a nasty issue introduced by changes in gdal_buildvrt behaviour in GDAL __ 2.3, (https://trac.osgeo.org/gdal/ticket/3221#comment:5) which caused problems in proper applic...

Read more »

Paid in Books: An Interview with Christian Westergaard

March 6, 2019
By
Paid in Books: An Interview with Christian Westergaard

R is greatly benefiting from new users coming from disciplines that traditionally did not provoke much serious computation. Journalists1 and humanist scholars2, for example, are embracing R. But, does the avenue from the Humanities go both ways? In a recent conversation with Christian Westergaard, proprietor of Sophia Rare Books in Copenhagen, I was delighted to learn that it does. JBR:...

Read more »

Quick post – detect and fix this ggplot2 antipattern

March 6, 2019
By
Quick post – detect and fix this ggplot2 antipattern

Recently one of my coworkers showed me a ggplot and although it is not wrong, it is also not ideal. Here is the TL:DR : Whenever you find yourself adding multiple geom_* to show different groups, reshape your data In software engineering there are things called antipatterns, ways of programming that lead you into potential trouble. This is one of them. I’m not...

Read more »

See you in Barcelona this summer

March 6, 2019
By
See you in Barcelona this summer

Have you been feeling lately that you are missing out the coolest skill-set in academia? Here is you chance to cut in and dive into R. In July BaRacelona Summer School of Demography welcomes dedicated scholars, aspiring or established, to help th...

Read more »

76th Tokyo.R Users Meetup Roundup!

March 6, 2019
By
76th Tokyo.R Users Meetup Roundup!

The 76th Tokyo R User Meetup happened on March 2nd, graciously hosted by DeNA (an entertainment and e-commerce company) in their lovely headquarters located in Shibuya. (Photo courtesy of Takashi Minoda) On this day anot...

Read more »

The ggforce Awakens (again)

March 6, 2019
By
The ggforce Awakens (again)

After what seems like a lifetime (at least to me), a new feature release of ggforce is available on CRAN. ggforce is my general purpose extension package for ggplot2, my first early success, what got me on twitter in the first place, and ultimately instrumental in my career move towards full-time software/R development. Despite this pedigree ggforce haven’t really received much love in the...

Read more »

Efficient landscape metrics calculations for buffers around sampling points

Efficient landscape metrics calculations for buffers around sampling points

Landscape metrics are algorithms that quantify physical characteristics of landscape mosaics (aka categorical raster) in order to connect them to some ecological processes. Many different landscape metrics exist and they can provide three main levels of information: (i) landscape level, (ii) class level, and (iii) patch level. A landscape level metric gives just one value describing a certain property of a...

Read more »

At the end of the rainbow

March 6, 2019
By
At the end of the rainbow

Fully saturated RGB rainbow colors are still widely used in scientific visualizations despite their widely-recognized disadvantages. A recent wild-caught example is presented, showing its limitations along with a better HCL-based alternative ...

Read more »

R vs Python: Which is better for Data Science?

March 6, 2019
By
R vs Python: Which is better for Data Science?

Since, R and Python remain the most popular languages, it seems reasonable to debate which one is better. We'll evaluate the two languages in four categories: Data Visualization, Modelling Libraries, Ease of learning and Community support.

Read more »

Starting With Data Science: A Rigorous Hands-On Introduction to Data Science for Engineers

March 6, 2019
By

Starting With Data Science A rigorous hands-on introduction to data science for engineers. Win Vector LLC is now offering a 4 day on-site intensive data science course. The course targets engineers familiar with Python and introduces them to the basics of current data science practice. This is designed as an interactive in-person (not remote or … Continue reading Starting...

Read more »

International Summer School on Geospatial Data Science with R in Jena

March 6, 2019
By
International Summer School on Geospatial Data Science with R in Jena

We are proud to announce our “International Summer School on Geospatial Data Science with R” taking place at the GIScience department of Jena (Germany) from 25. August to 1. September 2019.

Read more »

Dataiku with RStudio integration

March 5, 2019
By
Dataiku with RStudio integration

Introduction Some time ago I wrote about the support for R users within Dataiku. The software can really boost the productivity of R users by having: Managed R code environments, Support for publishing of R markdown files and shiny apps … Continue reading →

Read more »

Building a Shiny app to show the impact of vaccines

Building a Shiny app to show the impact of vaccines

Debates about vaccines are ongoing in many countries and the debate has reblossomed in Denmark after we’ve had five recent occurrences of measels. While that is nothing compared to the measles outbreak currently ravaging Japan it is still enough to worry the health authorities that it might result in an epidemic. Here we’ll use Shiny to create an app that shows the impact of contagious diseases and the influence...

Read more »

Lots of zeros or too many zeros?: Thinking about zero inflation in count data

Lots of zeros or too many zeros?: Thinking about zero inflation in count data

In a recent lecture I gave a basic overview of zero-inflation in count distributions. My main take-home message to the students that I thought worth posting about here is that having a lot of zero values does not necessarily mean you have zero inflation. Zero inflation is when there are more 0 values in the data than the distribution allows...

Read more »

Bayesian Survival Analysis with Data Augmentation

March 5, 2019
By
Bayesian Survival Analysis with Data Augmentation

Motivation Model Set Up Data Augmentation Metropolis-in-Gibbs Sampler Simulation Example in R Motivation When dealing with time-to-event data, right-censoring is a common occurance. Although most are familiar with likelihood construction under ...

Read more »

Building a Shiny app to show the impact of vaccines

Building a Shiny app to show the impact of vaccines

Debates about vaccines are ongoing in many countries and the debate has reblossomed in Denmark after we’ve had five recent occurrences of measels. While that is nothing compared to the measles outbreak currently ravaging Japan it is still enough to worry the health authorities that it might result in an epidemic. Here we’ll use Shiny to create an app that shows the impact of contagious diseases and the influence...

Read more »

Getting started with RMarkdown & trying to make it in the world of Kaggle. Join MünsteR for our next meetup!

March 5, 2019
By
Getting started with RMarkdown & trying to make it in the world of Kaggle. Join MünsteR for our next meetup!

In our next MünsteR R-user group meetup on Tuesday, April 9th, 2019, we will have two exciting talks: Getting started with RMarkdown and Trying to make it in the world of Kaggle! You can RSVP here: http://meetu.ps/e/Gg5th/w54bW/f Getting started ...

Read more »

Graph analysis using the tidyverse

March 5, 2019
By
Graph analysis using the tidyverse

It is because I am not a graph analysis expert that I though it important to write this article. For someone who thinks in terms of single rectangular data sets, it is a bit of a mental leap to understand how to apply tidy principles to a more robust object, such as a graph table. Thankfully, there are two...

Read more »

Cancer clusters and the Poisson distributions

March 5, 2019
By
Cancer clusters and the Poisson distributions

On March 1, 2019, an article was published in Israel’s Ynetnews website, under the title “The curious case of the concentration of cancer”. The story reports on a concentration of cancer cases in the town of Rosh Ha’ayin in central Israel. In the past few years dozens of cases of cancer have been discovered in … Continue reading Cancer...

Read more »

Head’s Up! Roll Your Own HTTP Headers Investigations with the ‘hdrs’ Package

March 5, 2019
By
Head’s Up! Roll Your Own HTTP Headers Investigations with the ‘hdrs’ Package

I blathered alot about HTTP headers in the last post. In the event you wanted to dig deeper I threw together a small package that will let you grab HTTP headers from a given URL and take a look at them. The README has examples for most things but we’ll go through a bit of... Continue reading →

Read more »

How to become a Mango

March 5, 2019
By

At Mango, we talk a lot about going on a ‘data-driven journey’ with your business. We’re passionate about data and getting the best use out of it. But for now, instead of looking at business journeys, I wanted to talk to the Mango team and find out how they started on their own ‘data journey’ – what attracted them to a...

Read more »

Search R-bloggers

Sponsors