GGplot2 Mapping: Geospatial Analysis with R
This tutorial will introduce data exploration through geospatial analysis. We will cover basic mapping packages available in R and ggplot2 related issues. More advanced ggplot2 and tidyverse functions including filtering, summarizing, merging, and familiar concepts covered in previous lectures such as faceting and advanced aesthetics will also be touched on.
Note: Spatial data here is referring to any kind of data that contains geographical attributes (latitude, longitude, altitude) as part of its feature.
The goals of this tutorial are to explore data spatially and build custom data visualizations for specific objectives including:
- Bin/Tile mapping: an alternative technique for visualizing density/aggregation when working with large data sets.
- U.S. and Congressional district mapping: accessing, merging, and summarizing data.
- World and country mapping: accessing, merging, and summarizing across global data.
This tutorial is in R and R studio, an open source statistical package used by data scientists, statisticians, and other researchers. R is a widely-used open source tool that allows for both data analysis and data visualization using a multitude of methods that can be expanded upon quite easily. Some background knowledge of the software and statistics will be helpful.
Thank you!