See how to join two data sets by one or more common columns using base R’s merge function, dplyr join functions, and the speedy data.table package. R has a number of quick, elegant ways to join data ...

Data journalists generally use Microsoft Excel for analysing data. Why? Well when you run Windows on your machine, Word will most likely be your text editor and Excel ...

Data clustering is the process of programmatically grouping items that are made of numeric components. For example, suppose you have a dataset where each item represents a person's age, annual income ...

I 'm a big fan of Python for data analysis, but even I get curious about what else is available. R has long been the go-to language for statistics, but the "Tidyverse" has given the language a serious ...

An understanding and working knowledge of the basic principles of statistics are of central importance in understanding the sport and health sciences. Introduction to Statistics in Human Performance: ...

Designed to introduce students to quantitative methods in a way that can be applied to all kinds of data in all kinds of situations, Statistics and Data Visualization Using R: The Art and Practice of ...

R is hot. Whether measured by more than 10,000 add-on packages, the 95,000+ members of LinkedIn’s R group or the more than 400 R Meetup groups currently in existence, there can be little doubt that ...

The RNA-seq platform 1,2 addresses a multitude of applications, including relative expression analyses, alternative splicing, discovery of novel transcripts and isoforms, RNA editing, allele-specific ...

Do you want to analyze data that resides in Google BigQuery as part of an R workflow? Thanks to the bigrquery R package, it’s a pretty seamless experience — once you know a couple of small tweaks ...