Chapter 1: Get Started

Submission Requirement

You are required to submit a report for this lab. Please follow the instructions below, complete “Lab1 report” and submit it on Canvas.

1.1. Software Installation

1.1.1 R and RStudio

R is the based app to process R programming language, and RStudio integrates with R to provide further functionality such as graphical user interface (GUI). We need to install both R and RStudio for this workshop.

Note: there are R and RStudio installed in the computer lab. Please use the PCs in the lab if you cannot install.

1.1.2 Install R

We will install R first.

Windows users:

Please go to the website: https://cran.rstudio.com/
Download and install R
Download R for Windows
install R for the first time
Download R-4.4.1 for Windows (Remember the folder where you save it!!)
Go to the folder where you save the file “R-4.4.1-win.exe”, double click to run the installation, use default settings, click “Next” until the end
Finish

Mac users:

Please go to the website: https://cran.rstudio.com/
Download R for macOS
Under the “Latest release”, download the version that is suitable for your machine (“R-4.4.1-arm64.pkg” or “R-4.4.1-x86_64.pkg”) –> save
Go to the folder where you save the file, run the installation, use default settings, click “Next” until the end
Finish

1.1.3 Install RStudio

Next, we will install RStudio, the GUI of R.

Windows users:

Please go to: https://posit.co/download/rstudio-desktop/
Download RStudio desktop for windows, then Save
Go to the folder where you download the file “RStudio-2024.04.2-764.exe”
Run the installation, use default settings, click “Next” until the end
Finish

Mac users:

Please go to: https://posit.co/download/rstudio-desktop/
Scroll down
look for “macOS 12+”, click “RStudio-2024.04.2-764.dmg” and save
Go to the folder where you download the file
Run the installation, use default settings, click “Next” until the end
Finish

1.2. Good Practice - Organizing Folders

It happens to me all the time that my course A files are mixed with course B’s. To make things easier, I highly recommend organizing your folders in the following way:

Create a folder specifically for this course (e.g., Geoviz_fall_2024).
Under the course folder, create a series of sub-folders for different labs and assignments separately, for example, folders with “lab1”, “lab2”, “lab3”…..”assignment1”, “assignment2”….(see Figure 1.1)
For each lab, work in that specific folder. For example, for this lab, you could work in the “lab1” folder under the “Geoviz_fall_2024” course folder.

Figure 1.1: Creating a course folder and a series of sub-folders for labs

1.3. Launching RStudio

Remember that we have installed both R and RStudio earlier? But for this lab and for all future ones, we only need to run RStudio. This is because R is the hidden computing infrastructure while RStudio is the interface.

Run RStudio.

Figure 1.2: Lauching RStudio

If it is the first time to run RStudio, it may ask you to “select the version of R to use”. Use the default option “64-bit version of R”, click “OK”. “Enable automated crash reporting” –> “Yes”

After launching RStudio, you will see the following interface (Figure 1.3). Figure 1.3: The interface of RStudio

1.3.1 Create a project

Before creating a project, please make sure that you have already created your course folder and the sub-folder “lab1” as mentioned in Section 2: Good practice.

In RStudio menu –> File –> New Project –> Existing Directory –> Browse & Navigate to the course folder, then the sub-folder “lab1” –> Double clicks to go inside of the folder “lab1” –> Open –> Create Project

Note: we will need to repeat this to create projects for future labs and assignments.

1.3.1 Create a new script

A script is a sequence of instructions that can be executed by a computer or programming language (in our case, R). To create a new script, in RStudio menu –> New File –> R Script (see Figure 1.4)

Figure 1.4: New script

Then, we also need to save the script to the “lab1” folder. File –> Save –> Specify File Name –> Save (see Figure 1.5)

Figure 1.5: Save script to folder “lab1”

After creating and saving the new script, you should see something similar to Figure 1.6.
Figure 1.6: Interface after creating a new script

Let’s try to coding now. First, let’s ask the machine to do math for us.

Type the following command in the top-left window (red in Figure 1.6)
Select that line
click run

2+5+8

## [1] 15

Figure 1.7: Simple coding - math Next, let’s asking the machine to print some words for us. Type the following command and run it. Hint: to run codes, please select lines and click “Run”

print("GES Geovisualization")

## [1] "GES Geovisualization"

Good Coding Practice:

Always start a new line when writing a new command;
In R & RStudio, scripts are !!case-sensitive!! Changing the capitalization of codes can run into errors.

1.4. Let’s start mapping!

tmap is a commonly used package in R for mapping. We install this package first. Type the command in your script and click “run”.

install.packages("tmap")

Then, we load the tmap package. Again, type –> select –> run

# load "tmap"
library(tmap)

1.4.1. Hello World!

The package tmap itself has a dataset on countries. Let’s load the data first, and create a world map based on their level of inequality.

Please run the command below on your local machine. What do you see under the Plot tab on bottom right? Click “Zoom”. Please do a screenshot of the map and paste it to your “Lab1 Report”.

# load the world data
data("World")

# create a map
tm_shape(World) +
    tm_polygons("inequality")

Close the “Plot Zoom” window and go back to the script.

1.4.2 Interactive Map

Next, we will create an interactive map to explore countries’ happy planet index (HPI). The Happy Planet Index is a measure of sustainable well-being in considering human well-being and environmental impact.

We will use a different color palette (Yellow & Green) for this map. Type the code to your script –> select –> run.

tmap_mode("view")

tm_shape(World) +
    tm_polygons("HPI", palette = "YlGn")

Under the Plot tab, click “Zoom”. Please do a screenshot of the map and paste it to your “Lab1 Report”.
Hover over the map and click any country, you should be able to see their HPI index. Please report HPI indexes of any five countries to “Lab1 Report”.

1.5. Close & Exit

To close an R project, please go “File”–> “Close Project” – a pop window asking “Do you want to save these changes” –> “Yes”.