Monthly Archives: April 2016

New nasadata R package

April 30, 2016
By
New nasadata R package

This package intends to provide a hassle-free way to access some of NASA’s open-source API’s to build applications or models. Because the documentation seems inconsistent and there are tons of API’s, I have concentrated my efforts on three which I believe provide the best “bang for my money”. The source package is built around these three API’s, but for the sake...

Read more »

Register now for Hadley Wickham’s Master R in Amsterdam

April 30, 2016
By
Register now for Hadley Wickham’s Master R in Amsterdam

On May 19 and 20, 2016, Hadley Wickham will teach his two day Master R Developer Workshop in the centrally located European city of Amsterdam. This is the first time we’ve offered Hadley’s workshop in Europe. It’s a rare chance to learn from Hadley in person. Only 3 public Master R Developer Workshop classes are

Read more »

Introduction to R for Data Science

April 30, 2016
By
Introduction to R for Data Science

Branko Kovač Data Analyst at CUBE, Data Science Mentor at Springboard, Institut savremenih nauka, Data Science Serbia, and Goran S. Milovanović, [email protected], Data Science Serbia, are giving a free introductory course on R for Data Science in Belgrade, Serbia. All course materials - slides, R scripts, data sets, summaries and recommended readings - can be found on this page. The course is...

Read more »

Why I fart? (or how small data changes life)

April 30, 2016
By
Why I fart? (or how small data changes life)

I have had gas problem for quite a while. Usually, right after I have lunch, gas starts to accumulate in my belly. Then comes the fart. It was really annoying, especially when you sat in the front row of a class. Sometimes it was even painful as there are too much gas in the belly that somehow couldn’t get...

Read more »

Introduction to R for Data Science :: Session 1

April 30, 2016
By
Introduction to R for Data Science :: Session 1

Welcome to Introduction to R for Data Science Session 1! The course is co-organized by Data Science Serbia and Startit. You will find all course material (R scripts, data sets, SlideShare presentations, readings) on these pages. Lecturers dipl. ing Branko Kovač, Data Analyst at CUBE, Data Science Mentor at Springboard, Institut savremenih nauka, Data Science Serbia Goran S. Milovanović, Phd, [email protected], Data Science...

Read more »

Lattice exercises – part 1

April 30, 2016
By
Lattice exercises – part 1

In the exercises below we will use the lattice package. First, we have to install this package with install.packages("lattice") and then we will call it library(lattice) . The Lattice package permits us to create univariate, bivariate and trivariate plots. For this set of exercises we will see univariate and bivariate plots. We will use a

Read more »

Base R Nostalgia — by, tapply, ave, …

April 30, 2016
By
Base R Nostalgia — by, tapply, ave, …

photo credit: Paul Yoakum This evening I was feeling nostalgic for base R group-bys. Before there was dplyr, there was apply and its cousins. I thought it’d be nice to get out the ol’ photo-album. To start off, the base R proto-ancestor of magr...

Read more »

Base R Nostalgia — by, tapply, ave, …

April 30, 2016
By
Base R Nostalgia — by, tapply, ave, …

photo credit: Paul Yoakum This evening I was feeling nostalgic for base R group-bys. Before there was dplyr, there was apply and its cousins. I thought it’d be nice to get out the ol’ photo-album. To start off, the base R proto-ancestor of magrittr piping for me was the with function, especially with apply. It just cleaned up the syntax and visual...

Read more »

Identify, describe, plot, and remove the outliers from the dataset

April 30, 2016
By
Identify, describe, plot, and remove the outliers from the dataset

In statistics, a outlier is defined as a observation which stands far away from the most of other observations. Often a outlier is present due to the measurements error. Therefore, one of the most important task in data analysis is to identify and (if is necessary) to remove the outliers. There are different methods to Related PostLearn R By...

Read more »

Data science with Docker

April 29, 2016
By

Using docker to facilitate your data science pipelines Until recently, and like many other fellow data scientists I have talked to, I built data science pipelines on my local machine or a remote host while relying on virtual environments. In doing so, I ensured some degree of replicability by keeping check of language versions, library versions, and so on. While...

Read more »

Search R-bloggers

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)