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 ...

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 ...

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 ...

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 ...

The table below shows my favorite go-to R packages for data import, wrangling, visualization and analysis — plus a few miscellaneous tasks tossed in. The package names in the table are clickable if ...

Once you’ve installed and configured R to your liking, it’s time to start using it to work with data. Yes, you can type your data directly into R’s interactive console. But for any kind of serious ...

Make your R data.table code more efficient and elegant with these special symbols and operators. Plus, learn about the new fcase() function R data.table code becomes more efficient — and elegant — ...

We describe how to conduct a regression analysis for competing risks data. The use of an add-on package for the R statistical software is described, which allows for the estimation of the ...