What is DPLYR? Dplyr is a grammar of data manipulation, providing a consistent set of verbs that help you solve the most common data manipulation challenges. The next series of examples will show how you can use the shortcuts in Dplyr to achieve the results of traditional R data manipulation, ...

Introduction RKWard is a free and open source Graphical User Interface for the R software, one that supports beginners looking to point-and-click their way through analyses, as well as advanced programmers. You can think of it as a blend of … Continue reading →

The EARL London 2018 agenda is now available. Explore the schedule of keynotes, presentations, and lightning talks that cover a huge range of topics, including the best uses of Shiny, R in healthcare, using R for good, and R in finance. The brilliant lineup of speakers-who represent a wide range of ...

I’ve previously written about Google Scholar. Its usefulness and its instability. I just read a post by Jon Tennant on how to harvest Google Scholar data in R and I thought I would use his code as the basis to generate some nice plots based on Google Scholar data. ...

Here’s the problem: I have some data with nested time series. Lots of them. It’s like there’s many, many little datasets inside my data. There are too many groups to plot all of the time series at once, so I just want to preview a handful of ...

So far, we have learned how to count spatial variability in our model. Please look at these two previous exercises here and here if you haven’t tried it yet. However, it only represents 1-Dimension model. On this exercise, we will try to expand our spatial consideration into 2-Dimension model. ...

trekfont is now available on CRAN. This is a simple data package that exposes 107 Star Trek font families. You might not want to use Star Trek fonts for work, but if you are making plots for fun and like Star Trek then these fonts are for you. This post gives ...

Below are my “Top 40” picks from the approximately 212 new packages that made it to CRAN in April. They are organized into ten categories: Computational Methods, Data, Data Science, Machine Learning, Music, Science, Statistics, Time Series, Utilities, and Visualizations. Computational Methods diffeqr v0.1.1: Provides an interface to DifferentialEquations.jl which offers ...

The method agreement procedure Tweaking Credits The method agreement procedure When running a factor analysis, one often needs to know how many components / latent variables to retain. Fortunately, many methods exist to statistically answer this question. Unfortunately, there is no consensus on which method to use. Therefore, the n_factors() ...

In health services research, experiments are often conducted at the provider or site level rather than the patient level. However, we might still be interested in the outcome at the patient level. For example, we could be interested in understanding the effect of a training program for physicians on their ...

This is this second post of the “Create your Machine Learning library from scratch with R !” series. Today, we will see how you can implement K nearest neighbors (KNN) using only the linear algebra available in R. Previously, we managed to implement PCA and next time we will deal with ...

We’re finally here. Datazar Paper is the most exciting tool we’ve created to date. Up until now, I’d like to believe we’ve only made par with the status quo in terms of the tools we have developed for our beloved community of industry researchers, hackers and ...

In the exercises below, we will work with FFTree pacakge which lets us use fast and frugal decision tree to model the data Please install the package and load the library before starting Answers to these exercises are available here. If you obtained a different (correct) answer than those listed ...

taxize was seven years old this last Saturday! What is taxize? taxize is designed around making working with taxonomic names easier - abstracting away the details of what each of 20 or so taxonomic data sources require for a given use case. A samping of use cases covered in taxize (all ...

How long does it take you to install your complete GPU-enabled deep learning environment including RStudio or jupyter and all your packages? And do you have to do that on multiple systems? In this blog post series I’m going to show you how and why I manage my data ...