Creating Hexbin Maps in R - Revision history

Smitch: /* Installing Packages */ clarifying what ?? does in R (as opposed to just ?)

2022-01-07T16:40:48Z

Installing Packages: clarifying what ?? does in R (as opposed to just ?)

Smitch: /* Installing Packages */ fixed typo

2022-01-07T16:39:32Z

Installing Packages: fixed typo

Smitch: /* Objective */ edits to point out more precise use of the various "open" options

2022-01-07T16:36:37Z

Objective: edits to point out more precise use of the various "open" options

ODale: /* Adding Map Elements */

2021-12-13T22:02:02Z

Adding Map Elements

ODale: /* Adding Map Elements */

2021-12-13T22:01:10Z

Adding Map Elements

ODale: /* Symbolizing Data */

2021-12-13T22:00:28Z

Symbolizing Data

ODale: /* Importing Data */

2021-12-13T21:58:40Z

Importing Data

ODale: /* Installing Packages */

2021-12-13T21:55:19Z

Installing Packages

ODale: /* Navigating RStudio */

2021-12-13T21:54:10Z

Navigating RStudio

ODale: /* Navigating RStudio */

2021-12-13T21:52:45Z

Navigating RStudio

@@ Line 108: / Line 108: @@
 library(rgeos)</syntaxhighlight>
-'''TIP:''' If you want to learn more about a specific package or function, you can write a command to view the corresponding 'Help' page. In the script window you can run <code>help()</code> or type the name of the function preceded by a question mark in the R console, for example <code> ?brewer.pal</code> (see Figure 5). If the package or function is not found in your library, you can still access the documentation by using two question marks, for example <code>??brewer.pal</code>. The R documentation will provide a description, a list of arguments, details, references, as well as a number of examples (see Figure 5 for an example).
+'''TIP:''' If you want to learn more about a specific package or function, you can write a command to view the corresponding 'Help' page. In the script window you can run <code>help()</code> or type the name of the function preceded by a question mark in the R console, for example <code> ?brewer.pal</code> (see Figure 5). If the package or function is not found in your library, you can still access the documentation by searching the entire help library, by using two question marks at the prompt, for example <code>??brewer.pal</code>. The R documentation will provide a description, a list of arguments, details, references, as well as a number of examples (see Figure 5 for an example).
 [[File: hexbinhelp.png|500px]]

@@ Line 82: / Line 82: @@
 === Installing Packages ===
-R enables users to install and load packages from the CRAN. A package is a shareable bundle of code, sample data, documentation and tests. R packages are an advantage of this piece of software as they allow users to easily share their code with others. In additional to the pre-installed base package, we will need to download additional packages for this tutorial. Click the link beside each package listed below to learn more. Install the required packages using the below script. Once installed, we have to call each of the pacakges from our library. Alternatively, you can use the 'Install Packages' dialog box which is accessible through the main menu (Tools > Install Packages).
+R enables users to install and load packages from the CRAN. A package is a shareable bundle of code, sample data, documentation and tests. R packages are an advantage of this piece of software as they allow users to easily share their code with others. In additional to the pre-installed base package, we will need to download additional packages for this tutorial. Click the link beside each package listed below to learn more. Install the required packages using the below script. Once installed, we have to call each of the packages from our library. Alternatively, you can use the 'Install Packages' dialog box which is accessible through the main menu (Tools > Install Packages).
 *'''tidyverse''' [https://cran.r-project.org/web/packages/tidyverse/index.html Learn more]

@@ Line 1: / Line 1: @@
 == Objective ==
-The objective of this tutorial is to create a thematic hexbin map of U.S. higher education in RStudio. Users will learn how to create a hexbin map from a geospatial object and plot thematic data. In addition, this tutorial will demonstrate how to add and customize various cartographic elements to your map including symbolization, labelling, and map elements (e.g., title, legend). Users will have the opportunity to become more familiar with the R programming language as well as explore the spatial and cartographic capabilites of the software. This tutorial uses open-source software and data and will discuss the advantages and limitations of each. Finally, this tutorial contributes to the collection of Open Source GIS tutorials created by students at Carleton University.
+The objective of this tutorial is to create a thematic hexbin map of U.S. higher education in RStudio. Users will learn how to create a hexbin map from a geospatial object and plot thematic data. In addition, this tutorial will demonstrate how to add and customize various cartographic elements to your map including symbolization, labelling, and map elements (e.g., title, legend). Users will have the opportunity to become more familiar with the R programming language as well as explore the spatial and cartographic capabilites of the software. This tutorial uses open-source software and open data and will discuss the advantages and limitations of each. Finally, this tutorial contributes to the collection of Open GIS tutorials created by students at Carleton University.
 '''Software Requirements:''' R, RStudio, spreadsheet software (e.g., Microsoft Excel)

@@ Line 208: / Line 208: @@
 centers <- cbind.data.frame(data.frame(gCentroid(hex, byid=TRUE), id=hex@data$iso3166_2))</syntaxhighlight>
-A '''legend''' can be created and added to our map to help the viewer understand what each colour symbol represents. The legend should include a title as well as labels that indicate the data range for each symbol. Different functions found within the <code> ggplot2</code> package allow us to add a legend to our map and customize its size, type colour, background colour and position.
+A '''legend''' can be created and added to our map to help the viewer understand what each colour symbol represents. The legend should include a title as well as labels that indicate the data range for each colour symbol. Different functions found within the <code> ggplot2</code> package allow us to add a legend to our map and customize its size, type colour, background colour and position.
 Arguments for <code> guide.legend</code>:

@@ Line 202: / Line 202: @@
 === Adding Map Elements ===
-'''Labels''' can be added to our map to provide viewers with geographic reference information. This is especially important for our hexbin map where the U.S. states boundaries are not positioned or shown as they would appear on a political map. To add labels to the hexbin map, we must first calculate the centroid of each hexagon using the <code> gCentroid</code> function. Next, we will use the two-letter state abbreviations in the "id" field. The labels will be added to the plot using the <code> geom_text</code> function. The colour and size of the labels can also be changed.
+'''Labels''' can be added to our map to provide viewers with geographic reference information. This is especially important for our hexbin map where the U.S. states boundaries are not positioned or shown as they would appear on a political map. To add labels to the hexbin map, we must first calculate the centroid of each hexagon using the <code> gCentroid</code> function. Next, we will create our labels using the two-letter state abbreviations in the "id" field. The labels will be added to the plot using the <code> geom_text</code> function. The colour and size of the labels can also be changed.
 <syntaxhighlight lang="R">

@@ Line 173: / Line 173: @@
 Choropleth maps are a common type of thematic map that portray geographic patterns for areal units such as states and provinces. They generally consist of two to six colour symbols which represent a corresponding number of nonoverlapping classes for an intensity index (Monmonier, 2018).
-To symbolize the attribute data in our choropleth map, we will use graduated colour symbology. By varying the colours of the hexagons, our map will show the quantiative difference in the number of Bachelor's Degrees awarded in Science and Engineering (per 1,000 indiviuduals) in the age cohort of 18-24 between the U.S. states in 2019. This visualization method will allow us to observe and analyse geographic patterns in the mapped variable. We will classify the data into ranges and assign a specific colour to each of the classes. When selecting the size and total number of classes, it is important to explore the distribution and central tendencies descriptive of our data. Too many classes can make our map overly complex and potenially confuse viewers. On the other hand, too few classes can oversimplify our data.
+To symbolize the attribute data in our choropleth map, we will use graduated colour symbology. By varying the colours of the hexagons, our map will show the quantiative difference in the number of Bachelor's Degrees awarded in Science and Engineering (per 1,000 indiviuduals) in the age cohort of 18-24 between the U.S. states in 2019. This visualization method will allow us to observe and analyse geographic patterns in the mapped variable. We will classify the data into ranges and assign a specific colour to each of the classes. When selecting the size and total number of classes, it is important to explore the distribution and central tendencies of our data. Too many classes can make our map overly complex and potentially confuse viewers. On the other hand, too few classes can oversimplify our data.
-The <code> RColorBrewer</code> package contains a number of ready-to-use colour palettes for creating graphics including maps. Users can choose from sequential (multi-hue and single cue), diverging, and qualitiative colour palettes, or users can create their own colour palettes using HEX codes. We can use the <code> display.brewer.all(colorblindFriendly=TRUE)</code> function to view ColorBrewer palettes that are colourblind-friendly (Figure 8). To create your own paletteo or to learn more, the ColorBrewer tool can be explored [https://colorbrewer2.org/ HERE]
+The <code> RColorBrewer</code> package contains a number of ready-to-use colour palettes for creating graphics including maps. Users can choose from sequential (multi-hue and single cue), diverging, and qualitiative colour palettes, or users can create their own colour palettes using HEX codes. We can use the <code> display.brewer.all(colorblindFriendly=TRUE)</code> function to view ColorBrewer palettes that are colourblind-friendly (Figure 8). To create your own palette or to learn more, the ColorBrewer tool can be explored [https://colorbrewer2.org/ HERE]
 <syntaxhighlight lang="R">

@@ Line 115: / Line 115: @@
 === Importing Data ===
-Before reading your data into R, ensure that your data are located in the folder that you set as your working directory.
+Before reading your data into R, ensure that they are located in the folder that you set as your working directory in the previous step.
 To import the hexbin data, we will use the <code> geojson_read()</code> function and assign it to a variable called "hex". The data will now appear in the 'Global Environment' tab in the top-right pane. After the file has been imported, we will need to reformat our data using the <code> mutate</code> and <code> gsub</code> functions and fortify it using the <code> tidy</code> function. At this stage, we can plot a basic version of our map using the fortified data (Figure 6).
 <syntaxhighlight lang="R">#Import hexbins
-hex <- geojson_read("us_states_hexgrid.geojson", what = "sp")
+hex <- geojson_read("us_states_hexgrid.geojson", what = "sp") #where "sp" is spatial class
 #Reformat the 'google_name' field
@@ Line 147: / Line 147: @@
 <syntaxhighlight lang="R">#Import education data
 #Note: my file name is bachelor.csv
-bach <- read.csv("bachelor.csv", header=T)
+bach <- read.csv("bachelor.csv", header=T) #indicate that the first row (header) contains the variable names
 #Remove rows and columns with NA values
 bach <-bach[-c(53:54), ] #rows

@@ Line 76: / Line 76: @@
 #December 2021</syntaxhighlight>
-'''TIP:''' RStudio allows users to change the theme of the IDE's user interface. The 'Modern' theme is the default, however you switch to a darker palette if you prefer. Learn how [https://support.rstudio.com/hc/en-us/articles/115011846747-Using-Themes-in-the-RStudio-IDE HERE].
+'''TIP:''' RStudio allows users to change the theme of the IDE's user interface. The 'Modern' theme is the default, however you can switch to a darker palette if you prefer. Learn how [https://support.rstudio.com/hc/en-us/articles/115011846747-Using-Themes-in-the-RStudio-IDE HERE].
 == Creating a Choropleth Map ==

@@ Line 57: / Line 57: @@
 # (Top left): '''Script window''' (Create and work on multiple scripts; Write and run your code)
 # (Bottom left): '''R console''' (View the results of a command and error messages)
-# (Top right): '''Environment''' (View a list of your created variables); '''History'''
+# (Top right): '''Environment''' (View a list of your created variables); '''History''' (View the command history of your session)
 # (Bottom right): '''Plots''' (View and save your graphs and maps); '''Packages''' (Explore available packages); '''Help''' (View R documentation and manuals)