Repository for my talk on April 28th, 2022 at the New York Open Statistical Programming Meetup Group.
Geospatial data is becoming increasingly common across domains and industries. Spatial data is no longer only in the hands of soil scientists, meteorologists, and criminologists, but in marketing, retail, finance, etc. It is common for spatial data to be treated as any other tabular data set. However, there is information to be drawn from our data's relation to space. The standard exploratory data analysis toolkit will not always suffice. In this talk I introduce the basics of exploratory spatial data analysis (ESDA) and the {sfdep} package. {sfdep} builds on the shoulders of {spdep} for spatial dependence, emphasizes the use of simple features and the {sf} package, and integrates within your tidyverse-centric workflow. By the end of this talk users will understand the basics of ESDA and know how to start incorporating these skills in their own work.
Josiah Parry is a Research Analyst in the Research Science division at The NPD Group focusing on modernization and methodology. Formerly he worked at RStudio, PBC on the customer success team enabling public sector adoption of data science tools. Josiah received his master's degree in Urban Informatics from Northeastern University. Prior to that, he earned his bachelor's degree in sociology with focuses in geographic information systems and general mathematics from Plymouth State University.
Note, presently under construction.
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