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.

Being a Data Scientist requires professional education, a sharp skill set, extensive training, experience, and expertise in the field to prosper in your career.

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.