To stay on top of R in the news, we’re sharing some stories related to R published last week. A great interview with JJ Allaire, creator of RStudio.(Joseph Rickert) The man who build RStudio now 13 years ago shares some insight on the company and his own motivation. Or was it a company? we are […]

## Optimize Data Exploration With Sapply() – Exercises

The apply() functions in R are a utilization of the Split-Apply-Combine strategy for Data Analysis, and are a faster alternative to writing loops. The sapply() function applies a function to individual values of a dataframe, and simplifies the output. Structure of the sapply() function: sapply(data, function, …) The dataframe used for these exercises: dataset1 <- […]

## Big Salaries, Recommendation Systems, and Where We’ll Be 5 Years from Now

To stay on top of R in the news, we’re sharing some stories related to R published last week. Why Data Science ‘Rock Stars’ Earn Big Salaries (Dennis McCafferty) Recent post and slide deck related to the 2016 Data Science Salary Survey (O’Reilly Media), with R mentioned as one of the high-demand programming languages (next […]

## How can we improve R-exercises?

Hey there! We’ve been sharing R exercise sets for about a year, and think this is a good moment to reflect and ask for your feedback. So here is your opportunity to have a say in where we take R-exercises next! We’d like to hone in a bit on the degree of difficulty of the […]

## Creating Sample Datasets – Exercises

Creating sample data is a common task performed in many different scenarios. R has several base functions that make the sampling process quite easy and fast. Below is an explanation of the main functions used in the current set of exercices: 1. set.seed() – Although R executes a random mechanism of sample creation, set.seed() function […]

## Dates and Times – Simple and Easy with lubridate Exercises (part 3)

Welcome to the third and last part of the “lubridate” exercises. If you missed Part 1 and 2 then please refer to the links below: Part 1 Part 2 In this part, I’ll cover the following topics: 1. Durations (exact spans of time) 2. Periods (relative spans of time) 3. Rounding dates As always, in […]

## Network Analysis Part 2 Exercises

In this set of exercises we shall practice the functions for network statistics, using package igraph.If you don’t have package already installed, install it using the following code: install.packages(“igraph”) and load it into the session using the following code: library(“igraph”) before proceeding. You can find more info about the package and graphs in general here […]

## R Course Finder update

A month ago we launched R course finder, an online directory that helps you to find the right R course quickly. With so many R courses available online, we thought it was a good idea to offer a tool that helps people to compare these courses, before they decide where to spend their valuable time […]

## One Way Analysis of Variance Exercises

When we are interested in finding if there is a statistical difference in the mean of two groups we use the t test. When we have more than two groups we cannot use the t test, instead we have to use analysis of variance (ANOVA). In one way ANOVA we have one continuous dependent variable […]

## Replicating Plots – Boxplot Exercises

R’s boxplot function has a lot of useful parameters allowing us to change the behaviour and appearance of the boxplot graphs. In this exercise we will try to use those parameters in order to replicate the visual style of Matlab’s boxplot. Before trying out this exercise please make sure that you are familiar with the […]