Tasklist

Readings

• R4DS Chapter 1
• R4DS Chapter 2
• Datacamp’s How to Make a Histogram with Basic R
• Datacamp’s How to Make a Histogram with ggplot

Tasks

• Create a new R script in RStudio
• Load the iris dataset with data(iris)
• Calculate the mean of the Petal.Length field
• Plot the distribution of the Petal.Length column as a histogram
• Save the script
• Click ‘Source’ in RStudio to run it from beginning to end

Readings

• Chapters 1-2 in R4DS
• Chapters 4-8 in Happy Git and Github for the useR - Installation

Tasks

• Create a GitHub account and post your github username here
• Install git on your computer
• Make sure git works in R-Studio
• Sign up for the GitHub Education pack
• Complete DataCamp Course in Introduction to R

Readings

• The ggplot2 vignette

Tasks

• Create a new R script in RStudio
• Load data from a comma-separated-values formatted text file hosted on a website
• Graph the annual mean temperature in June, July and August (JJA) using ggplot
• Add a smooth line with geom_smooth()
• Add informative axis labels using xlab() and ylab() including units
• Add a graph title with ggtitle()
• Save a graphic to a png file using png() and dev.off() OR ggsave
• Save the script
• Click ‘Source’ in RStudio to run the script from beginning to end to re-run the entire process

Readings

• Chapters 3 in R4DS
• Chapters 13-15 in Happy Git and Github for the useR - Installation
• Overview of Using the R-Studio GUI by R-Studio
• Chapter 8 R for Data Science - Projects
• RStudio and the Git GUI

Tasks

• Create a new repository for this course by following this link.
• Create a new project in Rstudio and connect it to the new repository in GitHub (these are labeled YEAR-GEO503-GITHUBUSERNAME). Helpful instructions are here
• Edit the README.md file in your repository to include a brief description of the repository (e.g. “Coursework for Spatial Data Science”).
• Stage and Commit your changes to Git (using the git tab in the upper right of RStudio)
• Push the repository up to GitHub

Readings

• The ggplot2 vignette
• R4DS Chapter 3 - Data visualization
• The Hans Rosling The River of Myths
• Watch the Hons Rosling video

Tasks

• Recreate layered graphics with ggplot including raw and transformed data
• Save graphical output as a .png file
• Save your script as a .R or .Rmd in your course repository

Readings

• Chapters 4-5 in R4DS

Tasks

• Quickly describe any functions that seem especially useful in the README.md file for this week.

Readings

• R4DS Chapter 13 - Relational Data

Tasks

• Join two datasets using a common column
• Answer a question that requires understanding how multiple tables are related
• Save your script as a .R or .Rmd in your course repository

Readings

• Chapters 11-13 in R4DS

Tasks

• Briefly describe functions that seem especially useful in the README.md file for this week.

Readings

• The Spatial Features Package (sf)

Tasks

• Reproject spatial data using st_transform()
• Perform spatial operations on spatial data (e.g. intersection and buffering)
• Generate a polygon that includes all land in NY that is within 10km of the Canadian border and calculate the area
• Save your script as a .R or .Rmd in your course repository

Readings

• Chapters 1-2 in GCR

Tasks

• Quickly describe functions that seem especially useful in the README.md file for this week.

Readings

• Raster Vector Interactions GCR

Tasks

• Calculate annual maximum temperatures from a monthly spatio-temporal dataset
• Remove Antarctica from the world dataset
• Summarize raster values within polygons
• Generate a summary figure and table.
• Save your script as a .R or .Rmd in your course repository

Readings

• Chapters 3-4 in GCR

Tasks

• Quickly describe functions that seem especially useful in the README.md file for this week.

Readings

• How to write a reproducible example
• Using Reprex package

Tasks

• Learn how to read R help files effectively
• Learn how to search for help
• Learn how to create a Minimum Working Example (MWE)
• Debug existing code
• Save your reprex to your course repository as an html file using Export -> “Save As Webpage” in the RStudio “Viewer” Tab.

Readings

• Chapters 3-4 in GCR

Tasks

• Complete project proposal and upload .Rmd and .md to Github

Readings

• Browse website about RMarkdown
• list(Browse [_R Markdown = “the Definitive Guide_](https://bookdown.org/yihui/rmarkdown/)”)

Tasks

• Create a new RMarkdown Document in Rstudio with File -> New File -> R Markdown and save it in the case_study folder for this session
• Click “Knit” button or File -> Knit Document to generate an HTML document
• Adjust the YAML header to produce a HTML, Word, and PDF version of the document.
• Save the outputs in your course folder for this week
• Think about how you could use this “one document, several outputs” approach in a project and make a few notes in your README.md file for this session.

Readings

• Chapters 11, 26-30 in R4DS
• Browse website about RMarkdown
• Browse details about creating RMarkdown Websites

Tasks

• Create repository for final project
• Explore various options for your project website
• Push changes back to GitHub
• Enable website on GitHub
• Complete DataCamp Course in Reporting with R Markdown

Readings

• Overview of the GHCN Dataset

Tasks

• Access and work with station weather data from Global Historical Climate Network (GHCN)
• Explore options for plotting timeseries
• Trend analysis
• Compute Climate Extremes

Readings

• GitHub Pull Requests

Tasks

• Commit your first draft of your project to GitHub

Readings

• Explore the DyGraphs webpage

Tasks

• Download daily weather data for Buffalo, NY using an API
• Generate a dynamic html visualization of the timeseries.
• Save the graph using Export->Save as Webpage

Readings

• GitHub Pull Requests
• Chapter 28 in R4DS

Tasks

• Review at least two other students’ projects and make comments via a pull request in GitHub before next class next week.
• Browse the Leaflet website and take notes in your readme.md about potential uses in your project. What data could you use? How would you display it?
• Browse the HTML Widgets page for many more examples. Take notes in your readme.md about potential uses in your project.

Readings

• NULL

Tasks

• Continue working on final project
• Come to class with any questions

Readings

• Chapter 23-25 in R4DS

Tasks

• Commit second draft of final project to GitHub for review
• Demonstrate a simple presence/absence model in spatial context.
• Model spatial dependence (autocorrelation) in the response.

Readings

• Wikipedia pages about Lightning talks
• Wikipedia pages about Ignite Sessions

Tasks

• Prepare to give your 5 minute presentation
• Present your analysis to your roommates, significant other, etc. and update your presentation based on the feedback
• Get feedback from 2-3 fellow classmates on your presentation and update it based on their feedback
• Give your 5 minute presentation in class

## Readings

Tasks

• Finalize your project and commit to GitHub
• Confirm the final version renders correctly on your website