Getting Started with RStudio is a project-based course provided by Coursera Project Network. It aims to focus on three learning objectives: Install R and RStudio on desktop, or use the new cloud-based solution that allows anyone to learn R, know the 10 most important things that 99% of R programmers should know about the RStudio IDE Interface and Be able to explain what R packages are, how to install and load them, from CRAN and Github, into the R session, and create interactive HTML widgets. The following are the notes I took during this course.

1. Install R and Get started with RStudio

Download and Install R via https://cloud.r-project.org/, and Download and Install RStudio via https://posit.co/downloads/ .

Using RStudio with the new cloud-based solution of RStudio via https://posit.cloud/ that allows anyone to do, share, teach and learn R, directly from your browser.

2. Most Important Features About RStudio

Know the 10 most important things that 99% of R programmers should know about the RStudio IDE Interface.

Within Tools > Global Options, you can change the theme of the code editor and the pane layout. Most developers will turn off Save .RData and History in the General tab of Gloabl Options as well.

A project is the fundamental unit of work in RStudio. It encapsulates your R code, packages and data files and provides isolation from other analyses.

3. Install and load R packages, from CRAN and Github.

The public clearing house for R packages is called CRAN, CRAN stands for Comprehensive R Archive Network.

Install the package dplyr which is used to manipulate data:

1

install.packages(“dplyr”); library(dplyr)

To download packages from Github, you need to download a package first, called devtoolsand it is on CRAN.

Download a package called broman from Github:

1

install_github("kbroman/broman")

4. Create and display interactive graphs and tables with 1 line of code.

Data sets in package broman:

1

data()

Show Violent Crime Rates by US State:

1

USArrests

The very common library to create interactive tables, interactive charts and interactive maps in R are DT, highcharter, leaflet.

Install the package DT from CRAN:

1
2

install.packages("DT")
library(DT)

Create a data table:

1

datatable(mtcars)

Create a Interactive map:

1
2
3

install.packages("highcharter")
library(highcharter)
hchart(mtcars, "scatter", hcaes(x=wt, y=mpg, z=drat, color=hp))

Create another map:

1
2
3

install.packages("leaflet")
library(leaflet)
leaflet() %>% addTiles() %>% setView(-85.39, 31.22, zoom=12)

The %>% sign called is called the pipe operator.

Bezhuang