R Programming

In the realm of skill acquisition, programming languages are akin to a toolkit of superpowers. Among these, 'R programming' stands out as a true marvel, capable of enhancing expertise across varied domains, from Power BI, Excel, to SQL. This article serves as a guiding light, illuminating the multifaceted ways in which mastering 'R programming' can elevate proficiency and unearth insights that were once beyond reach.

When comparing data sets, bar graphs can be a great analysis tool to utilise. In this article, we will dive into exactly how to get started making bar graphs in R.

A career within the mining industry can be both lucrative and rewarding, especially for those who enjoy hands-on practical work. In this article, we delve into the specifics and provide you with an overview of exactly how to become a miner.

Big data provides actionable results and insights that have made it a crucial component of today's tech world. To sort through such massive datasets and retrieve the right information, you must have the right tools and understand how to use them.

The R programming language is flexible; with versions available that run on UNIX, Windows and macOS platforms. The program has immense capabilities and knowing how to operate within the program is an asset.

One of our recent discoveries is BERT aka the Basic Excel R Toolkit. This is a package for working with the R programming language functions from Excel. It's a wonderful resource for adding functionality to Excel and best of all, it is free!

The R package, janitor, contains easy-to-use and convenient functions for basic data cleaning jobs and examining data. Let's take a look at some of these functions.

The data frame (or DataFrame) is an essential tool for anyone using R or Python to analyse data. They are rectangular or tabular data structures, that hold rows and columns of data, similar to tables in a database or an Excel spreadsheet.

We have recently been training a growing number of professionals in R and Python as they migrate from other code-based analytical packages such as MATLAB, Stata, SAS and SPSS. This post outlines some of the reasons for using code-based tools and why organisations are increasingly using Python and R for their data analysis needs.

The apply family of functions in R allow you to apply a function repeatedly to subsets of data in a single line of short code. Apply functions automatically to each column or row of data. Alternatively, apply functions to subsets of a data based on a category variable.

Both R and Python have a huge range of functionality available for working with data. Investing a few weeks to learn to use a programming language will enable you achieve big productivity gains.