R for beginners from zero

In these slides you will find content used to explain the world of R, so that you can get start to program easily. You will learn the difference between R and RStudio and the different types of data.

1. R for beginners from zero Cynthia SC (June 2nd, 2023) Member of Dr. Collado’s Team
2. What is R? • R is an open-source scripting language developed in 1993. ◦ It's an alternative implementation of the S programming language (1976). • The R environment is designed to perform complex statistical analysis and display results using visual graphics. • The R is written in C, Fortran, and R itself. ◦ Most R packages are written in the R itself, but heavy computational chucks are written in C, C++, and Fortran. • R allows integration with Python, C, C++, .Net, and Fortran too. • R is both a programming language and a software development environment.
3. How to start with R? You need both R and RStudio.
4. Do I need RStudio to interface with R? Do I need R to run code in RStudio? How can I run R code?
5. Is RStudio the only IDE available for R? Key Features: • User-friendly graphical user interface (GUI). • Great for beginners learning the R programming language for the first time. • Integrates well with other tools such as R Shiny, Add-ons, Git Version Control, and Rmarkdown. • Has lots of developer support.
6. Great support to produce a lot of graphs
7. Installation Pre-requisites: • R (4.2.3) or newer, latest is 4.3.0): https://cran.r-project.org/ • RStudio Version 2023.03.1+446 "Cherry Blossom" Release (2023-05-09) for macOS https://rstudio.com/products/rstudio/download/#download In the server: R version 4.3.0 Patched (2023-05-31 r84480) -- "Already Tomorrow" In local: R version 4.2.3 (2023-03-15) -- "Shortstop Beagle" What about the versions and flavors in R? What about the versions and flavors in RStudio? In local: 2023.03.1 Build 446 Go to help menu and then to About RStudio
8. EXPLORE the RStudio Integrated Development Environment (IDE)
9. Let’s go to RStudio 1. RStudio integrative development environment 2. Basic data types and common operations 3. Matrix and dataframe data structures
10. 1. RStudio environment
11. 2. Basic data types and common operations
12. 3. Matrix and dataframe data structures
13. Do you need help to start? You can request a Data Science guidance sessions (DSgs) with us! Here: https://lcolladotor.github.io/bioc_team_ds/data-science-guidance-sessions.html How? Scroll to the bottom of the page where the team member list is and request a particular 25 minute session, click on Calendly and any of us will get back to you ASAP. Looks like this:
14. Learning Resources http://research.libd.org/rstatsclub/#.XpB1SNNKiL8 http://research.libd.org/rstatsclub/20 18/12/24/r_101/