September, 2018 | R-bloggers

Data needs for forecasting influenza pandemics

September 16, 2018 | - r

Last week, I attended a Pandemic Influenza Exercise at the US CDC. To be clear, there is NOT a pandemic occuring right now, but the CDC ran this exercise where hundreds of staff members and outside observers and participants came together to practice g... [Read more...]

Tracking private R dependencies with packrat & git submodules

September 16, 2018 | Rstats on pi: predict/infer

Here at Methods we often use RStudio’s packrat package to version our package dependencies and help ensure our work is reproducible. Packrat handles public packages on CRAN or Github just fine, but we have a lot of internal packages hosted privately on Gitlab that we’d like to have ... [Read more...]

I’ll be talking at the R-Ladies Meetup about Interpretable Deep Learning with R, Keras and LIME

September 16, 2018 | Dr. Shirin Glander

Today I am very happy to announce that during my stay in London for the m3 conference, I’ll also be giving a talk at the R-Ladies London Meetup on Tuesday, October 16th, about one of my favorite topics: Interpretable Deep Learning with R, Keras and L... [Read more...]

How to create a sequential model in Keras for R

September 16, 2018 | Pablo Casas

This tutorial will introduce the Deep Learning classification task with Keras. With focus on one-hot encoding, layer shapes, train & evaluate the model.How to create a sequential model in Keras for R

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Data visualisation pitfalls: how to avoid barbarplots ?

September 16, 2018 | marion

You did an experiment or a survey, or you collected data, and you are ready to analyse them. But what is the first step? Everyone will tell you that you have to visualise your data with graphs. Yes, but how? and why? What are the common pitfalls to avoid? We ...

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Parameterizing with bquote

September 16, 2018 | John Mount

One thing that is sure to get lost in my long note on macros in R is just how concise and powerful macros are. The problem is macros are concise, but they do a lot for you. So you get bogged down when you explain the joke. Let’s try ... [Read more...]

Statistics Sunday: What Should I Read Next?

September 16, 2018 |

When You Need a New Book to Read I log all of my books on Goodreads. On top of that, whenever I hear about a new book I have to read, I add it on Goodreads, so I remember it. Of course, this means my Goodreads bookshelves are a little ... [Read more...]

Data Wrangling with dplyr – Part 3

September 15, 2018 | Rsquared Academy Blog

Introduction In the previous post, we learnt to combine tables using dplyr. In this post, we will explore a set of helper functions in order to: extract unique rows rename columns sample data extract columns slice rows arrange rows compare tables extract/mutate data using predicate functions count observations for ...

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Simple Parallel Processing in R

September 15, 2018 | Daniel Oehm

I recently purchased a new laptop with an Intel i7-8750 6 core CPU with multi-threading meaning I have 12 logical […] The post Simple Parallel Processing in R appeared first on Daniel Oehm | Gradient Descending. [Read more...]

Streamtubes in Plotly with Python

September 15, 2018 | Plotly Blog

???? Before we introduce this seriously cool visualization, we’d like to announce that plotly.py has surpassed 5 million downloads! Thank you for helping us reach this milestone! ???? Once Upon a Time ???? It was the year 2008. If you wanted to create 3-D plots for interactive scientific data visualization, the Mayavi Python ...

[Read more...]

Streamtubes in Plotly with Python

September 15, 2018 | Plotly Blog

???? Before we introduce this seriously cool visualization, we’d like to announce that plotly.py has surpassed 5 million downloads! Thank you for helping us reach this milestone! ???? Once Upon a Time ???? It was the year 2008. If you wanted to create 3-D plots for interactive scientific data visualization, the Mayavi Python ...

[Read more...]

Thunderstorm forecasting with GAMs

September 15, 2018 | Achim Zeileis

Boosted binary generalized additive models (GAMs) with stability selection and corresponding MCMC-based credibility intervals are discussed in a new MWR paper as a probabilistic forecasting method for the occurrence of thunderstorms. ...

[Read more...]

On “Competition” in the R Ecosystem

September 15, 2018 | John Mount

I’ve been thinking a bit on “competition” in the R ecosystem. I guess the closest I can come to a fair and coherent view on “competition” in the R ecosystem is some variation of the following. I, of course, should not be treating things as a competition. We are ... [Read more...]

How to Avoid For Loop in R

September 15, 2018 | statcompute

A FOR loop is the most intuitive way to apply an operation to a series by looping through each item one by one, which makes perfect sense logically but should be avoided by useRs given the low efficiency. In R, there are two ways to implement the same functionality of ... [Read more...]

Better R Code with wrapr Dot Arrow

September 15, 2018 | John Mount

Our R package wrapr supplies a "piping operator" that we feel is a real improvement in R code piped-style coding. The idea is: with wrapr‘s "dot arrow" pipe "%.__%" the expression "A %.__% B" is treated very much like "{. % B(.)" as a … Continue reading Better R Code with wrapr Dot Arrow [Read more...]

3 reasons to not write that new code, and how I failed at it

September 15, 2018 | Jozef's Rblog

Introduction We all know that feeling. We have this great idea about a new project, feature, function, piece of code. What do we want? Write that amazing new code! When do we want it? Right NOW! The aim of this post is to try and give you at 3 g...

[Read more...]

3 reasons to not write that new code, and how I failed at it.

September 15, 2018 | Jozef's Rblog

Introduction We all know that feeling. We have this great idea about a new project, feature, function, piece of code. What do we want? Write that amazing new code! When do we want it? Right NOW! The aim of this post is to try and give you at 3 good...

[Read more...]

Access to climate reanalysis data from R

September 15, 2018 | R on Dominic Royé

1 Introduction 2 NCEP 2.1 Packages 2.2 Data download 2.3 Monthly average 2.4 Visualization 3 ERA-Interim 3.1 Installation 3.2 Connection and download with the ECMWF API 3.3 Processing ncdf 4 Update for accessing ERA-5 A friend advised me to introduce R levels as categories. An idea that I now add to each blog post. There are three levels: elementary, intermediate, and ...

[Read more...]

Data Entry with R’s Text Editor

September 14, 2018 | George Mount

Excel’s greatest strength — and its greatest weakness — is the ease of users to manipulate the basic data. Done well and the capability affords flexibility; done poorly and you are left with hard-coded cells and hidden Column A’s. With R you approach the data differently by writing each step ... [Read more...]

How many deaths were caused by the hurricane in Puerto Rico?

September 14, 2018 | David Smith

President Trump is once again causing distress by downplaying the number of deaths caused by Hurricane Maria's devastation of Puerto Rico last year. Official estimates initially put the death toll at 15 before raising it to 64 months later, but it was clear even then that those numbers were absurdly low. The ... [Read more...]

R-bloggers

R news and tutorials contributed by hundreds of R bloggers

September 2018

Data needs for forecasting influenza pandemics

Tracking private R dependencies with packrat & git submodules

I’ll be talking at the R-Ladies Meetup about Interpretable Deep Learning with R, Keras and LIME

How to create a sequential model in Keras for R

Data visualisation pitfalls: how to avoid barbarplots ?

Parameterizing with bquote

Statistics Sunday: What Should I Read Next?

Data Wrangling with dplyr – Part 3

Simple Parallel Processing in R

Streamtubes in Plotly with Python

Streamtubes in Plotly with Python

Thunderstorm forecasting with GAMs

On “Competition” in the R Ecosystem

How to Avoid For Loop in R

Better R Code with wrapr Dot Arrow

3 reasons to not write that new code, and how I failed at it

3 reasons to not write that new code, and how I failed at it.

Access to climate reanalysis data from R

Data Entry with R’s Text Editor

How many deaths were caused by the hurricane in Puerto Rico?

September 2018

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