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 ...

After covering a recent session on data munging with Excel, I wanted to see how those tasks could be accomplished in R. Surely anything you can do in a spreadsheet should be doable in a platform ...

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 ...

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 ...

Before you can analyze and visualize data, you have to get that data into R. There are various ways to do this, depending on how your data is formatted and where it’s located. Usually, the function ...

Vectors, lists, arrays, matrices and data frames -- a look at five of the most fundamental data structures built into R. Among my colleagues, R is one of the fastest-growing programming languages.

R is the perfect language for creating a variety of chi-square tests, which are used to perform statistical analyses of counts of data. Here's how, with some sample code. A chi-square test (also ...