Technology Update

Abdullah Fathi

fotia.com.my

(MAMPU)

Introduction to R

History

R is a programming language
An implementation over S language
Designed by Ross Ihaka and Robert Gentleman at the University of Auckland in 1993
Stable released on 31 October 2014 (7 years ago), by R Development Core Team Under GNU General Public License

Benefit of using R

Open source
Cross Platform compatible
12000+ extensions/packages
Produce quality graph
Large user community
One of the fastest growing programming language
Connect with other languages
Able to integrate with powerful BI and ETL tools

Top 10 Programming Language Ranking

https://www.techrepublic.com/article/r-programming-language-continues-to-grow-in-popularity/

What is R uses for?

Statistical Inference
Data Analysis
Data Wrangling
Visualization
Machine Learning

R has the best mix of desirable attributes including high data science for business capability, low cost, growth, and has a massive ecosystem of powerful R libraries

R or Python?

These two titans can join forces through "reticulate" package which allows us to use Python and R together

Data Science Workflow Using R

R Stack

R & R Packages
RStudio
Shiny

R Package

Packages to expand the feature of R

1. Import Data

RDBMS (MySQL, MariaDB, MSSQL, Postgres, Oracle)
Non-Relational DB (mongo, cassandra)
File (csv, excel, txt, etc)
HDFS (Hadoop)
Web Scraping
Many more...

2. Data Wrangling (Dplyr)

2. Data Wrangling (Tidyr)

3. Data Exploration (DataExplorer)

Speed up data exploration process

https://cran.r-project.org/web/packages/DataExplorer/vignettes/dataexplorer-intro.html

create_report(df)

4. Data Visualization

4. Data Visualization (other)

Base R
d3r (d3.js)
rcharts
ggvis
rgl (3d plot)
patchwork (combine seperate ggplot into same graphic)
many more...

Integrated Development Environment

What is RStudio?

Add-on to R
User-friendly graphical interface

RStudio (IDE)

RStudio Edition

RStudio Desktop
- Premier IDE for R
RStudio Server
- RStudio anywhere using a web browser
RStudio Workbench
(Previously known as Rstudio Server Pro)
- Enterprise edition
- Adds many enhancements to the open-source version of RStudio Server

RStudio Workbench Features

Authentication (ActiveDirectory, LDAP, SAML, OpenID, or Google Accounts)
High-Availability and Load Balancing
Multiple versions of R
Multiple R sessions per user
Security features
Support for Jupyter, JupyterLab, and VS Code editor sessions
Project sharing for easy collaboration within workgroups
Administrative dashboard that provides insight into active sessions, server health, and monitoring of system-wide and per-user performance and resource metrics
Establish CPU priorities and memory limits for users or groups

https://docs.rstudio.com/ide/server-pro/?_ga=2.160924473.502842934.1623210458-1577041578.1623210458

Shiny Dashboard

Build an interactive web applications for visualizing data. Bring R data analysis to life.

Contains R functions for common HTML structures, UI Controls (Components/Widgets), and web framework tools. The framework is highly flexible, but require more knowledge of HTML & CSS