B. Krzyzanowski |
teaching resources & course materials
Spatial Data in r
Course Overview: We are living in a Big Data Era and finding that there is a deluge of data available for exploring questions about our world. With this much data comes a heightened need for efficient data management practices, powerful processing techniques, and streamlined analytical and visualization strategies. Working with vast quantities of complex spatial data has become commonplace within geographical information science (GIS). This course will introduce students to basic data management techniques that can be used to process Big Spatial Data within R Project (an open-sourced data management and statistical software). The data manipulation tasks that students tackle in this course will likely not be anything new to them. Lab assignments cover basic data transformation tasks such as collapsing tables, converting data types, and performing spatial joins. Most of these tasks can be easily accomplished outside of R with software such as ArcMap or Excel. However, when working with multiple inputs that contain thousands of records, these such tasks become impractical in standard GIS platforms. A well-written script in R can handle these tasks with just a click of a button.
R BootCamp Demo |
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