Introduction to R syntax: part 2: factors, matrices, arrays, lists, and data frames
Introduction to R syntax: part 2: factors, matrices, arrays, lists, and data frames Online
In these tutorials you will learn to read and write R scripts to do computations, data manipulation, and simple analysis. You will get hands-on coding experience via a web application, no software installation is required to attend. The goal is to explain the rules of the R syntax in general terms so you can make more sense of an introductory book or of the recipes you will find when searching for solutions on the internet. This tutorial is full of short exercises and code examples and it is directed to undergraduate or graduate students interested in learning R to apply it in assignments, projects, or theses but with no programming experience.
Part 1 (Jan 3 @ 12) covers using operators, expressions, variables, and built-in functions in R. Understanding assignment and how arguments work when calling functions. The data types and structures R offers to model data. Introduction to vectors. Part 2 (Jan 5 @ 12) covers the remaining data structures to model and manipulate data: factors, matrices, arrays, lists, and finally, the workhorse of data analysis, the data frame. We will study the basics of subsetting and ordering for data structures. Finally, we will have a look at user functions and basic control flow.
This workshop is taught by Pablo Adames. Pablo is a professional engineer in the province of Alberta with Masters in chemical and software engineering. His career has involved R&D, software development, and technical training in engineering software applications in Oil and Gas production simulation, real-time event identification, transportation process management, and computer vision. He has worked for companies like Neotec Consultants, Schlumberger, VMG Group, Fotec Solutions, and Canadian Pacific Railways, and is currently with IntelliView Technologies.
Pablo is a co-leader in the CalgaryR group and has presented several Technical Conference papers, the more relevant data analysis has to do with flow model classification using clustering, optimal parameter selection in flow models, and improving recommendation systems for charitable donations.
- Thursday, January 5, 2023
- 12:00pm - 1:30pm
- Time Zone:
- Mountain Time - US & Canada (change)
- This is an online event. Event URL will be sent via registration email.