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
  • Click Download R for Windows
  • Click install R for the first time
  • Download R-4.5.1 for Windows (Remember the folder where you saved it!!)
  • Go to the folder where you save the file “R-4.5.1-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/
  • Click Download R for macOS
  • Under the Latest release, download the version that is suitable for your machine (“R-4.5.1-arm64.pkg” or “R-4.5.1-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/
  • Under 2: Install RStudio click on Download RStudio desktop for windows, then Save
  • Go to the folder where you download the file “RStudio-xxxx.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 13+, click RStudio-2025.05.1-513.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).
  • 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 different tasks, work in their specific folders. For example, for this lab, you should 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

Earlier, we have installed both R and RStudio. But for this and all future labs, 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
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
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”
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 the lines you want to run 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.
  • When creating new variables, avoid spaces by using underscore “\(_\)”. For example, “city\(_\)boundary” is a good variable name, but “city boundary” will cause 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 the world’s countries. Let’s load the data first. On the top-right panel ‘Global Environment’, there is a variable called ‘World’. You can see the detailed data in the variable by clicking on it.

# load the world data
data("World")
## Warning in data("World"): data set 'World' not found

Figure 1.8: Variables in Global Environment Figure 1.9: Variables in Global Environment

Next, we 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? You should see a map similar to the screenshot below.

[Q] Click “Zoom” and capture a screenshot of the map and paste it to your “Lab1 Report”. Close the “Plot Zoom” window and go back to the script.

# create a map
tm_shape(World) +
    tm_polygons("inequality")
Figure 2.0: Static Map
Figure 2.0: Static Map

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")

[Q] Under the Plot tab, click “Zoom”. Please do a screenshot of the map and paste it to your “Lab1 Report”.
[Q] 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”.

Figure 2.1: Interactive Map
Figure 2.1: Interactive Map


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”.

Figure 1.8: Close & Save an R Project