Exploring Data with the Tidyverse
The tidyverse is a powerful collection of packages following a standard set of principles for usability. During this workshop David will demonstrate an exploratory data analysis in R using tidy tools. He will demonstrate the use of tools such as dplyr and ggplot2 for data transformation and visualization, as well as other packages from the tidyverse as they're needed. He'll narrate his thought process as attendees follow along and offer their own solutions. The workshop expects some familiarity with dplyr and ggplot2—enough to work with data using functions like mutate, group_by, and summarize and to create graphs like scatterplots or bar plots in ggplot2. These concepts will be re-introduced to ensure a smooth workshop, but it isn't designed for brand new R programmers. The workshop is designed to be interactive and participants are expected to type along on their own keyboards.
Geospatial Statistics and Mapping in R
Geospatial expert and Columbia Professor Kaz Sakamoto is leading this class on all things GIS. You'll learn how about map projections, spatial regression, plotting interactive heatmaps with leaflet and working with shapefiles. This course is designed for those who have familiarity with R and want to explore working spatial data into their work. The AM session will be an introduction to Geographic Information Systems(GIS), spatial features (sf package), Coordinate Reference Systems(CRS), and map making basics. The PM session will introduce spatial operations, geometric operations, statistical geography, spatial point pattern analysis and geostatistics. By the end of the day participants should be able to read/work with spatial data, understand projections, utilize geoprocessing techniques, and gain basic spatial statistics comprehension.
Git for Data Science
Daniel Chen, author of Pandas for Everyone, has given multiple talks at the New York R Conference about the data science workflow. In this workshop he'll teach how to use Git and project management for better organization and faster iteration. This workshop will have four parts: 1) Git on Your Own, 2) Working with Remotes, and 3) Git with Branches, and 4) Collaborating with Git. Part I will cover creating a git repository, adding and committing files, looking at differences between files, looking at your history, moving around your history, reverting changes, and undelete files. Part II will go over going from your computer to a remote (e.g., GitHub, BitBucket, GitLab), syncing your files by pushing and pulling, and conflicts. Part III will cover creating branches, moving around different branches, making commits in branches, merging branches, using branches with remotes, pull requests (aka, merge requests), merging pull requests, and syncing up with your remote. In Part IV, we will discuss how the skills you learned directly apply to collaboration with other people.