Geospatial Data, Maps & Spatial Analysis

R Geospatial Fundamentals: Parts 1-2

February 25, 2025, 2:00pm
In this 2-part workshop series, we will provide an introduction to spatial analyses in R. We discuss the benefits of the additional ‘location' component that defines spatial data and how spatial data frames organize this information. Using the sf (simple features) and terra packages, we'll navigate fundamental operations for reading, writing, manipulating, and visualizing spatial data.

Python Geospatial Fundamentals: Parts 1-2

March 4, 2025, 10:00am
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The Python programming language is a great platform for exploring these data and integrating them into your research.

Python Geospatial Fundamentals: Parts 1-2

November 4, 2024, 8:00am
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The Python programming language is a great platform for exploring these data and integrating them into your research.

Alex Ramiller

Senior Data Science Fellow 2024-2025, Data Science Fellow 2023-2024
City and Regional Planning

I am a PhD Candidate in City and Regional Planning. My research focuses on the use of large administrative datasets to study residential mobility, neighborhood change, and housing access. I received a Master in Geography from the University of Washington and a Bachelor's in Economics and Geography from Macalester College. I have also consulted on analytical projects for several organizations including the San Francisco Federal Reserve Bank, PolicyLink, and the City of Seattle.

R Geospatial Fundamentals: Parts 1-3

October 14, 2024, 2:00pm
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research. This workshop focuses on fundamental operations for reading, writing, manipulating and mapping vector data, which encodes location as points, lines and polygons.

Theo Snow

Availability: By appointment only

Consulting Areas: Python, R, SQL, SAS, Databases & SQL, Data Manipulation and Cleaning, Data Science, Data Visualization, Geospatial Data, Maps & Spatial Analysis, Machine Learning, Mixed Methods, Qualitative methods, Surveys, Sampling & Interviews, Regression Analysis, Means Tests, Software Output Interpretation, Other, Excel, Git or Github, RStudio, RStudio Cloud, SAS, Tableau

Emma Lasky

Availability: By appointment only

Consulting Areas: Python Programming, R Programming, Data Manipulation and Cleaning, Data Science, Data Sources, Data Visualization, Geospatial Data, Maps & Spatial Analysis, Mixed Methods, Regression Analysis, ArcGIS Desktop, Online or Pro, Excel, Git or Github, QGIS, RStudio, RStudio Cloud

Anusha Bishop

Availability: By appointment only

Consulting Areas: Python, R, Cloud & HPC Computing, Data Sources, Data Visualization, Geospatial Data, Maps & Analysis, Machine Learning, Research Design, Cluster analysis, Experimental design, Hierarchical Models, High dimensional statistics, Means Tests, Nonparametric methods, Regression Analysis, Software Output Interpretation, Spatial statistics, Bash or Command Line, Excel, Git or Github, RStudio

Kurt Soncco Sinchi

Consultant
Civil Engineering

First generation student and looking to improve and apply Data Science core concepts into social impactful projects, as well as trying to leverage the information from previous cases for better insights of society. Focused on infrastructure and its impact under natural disasters.

Severin Saenz, MCP

Academic Program Manager III, Consultant
Department of City and Regional Planning

I'm a graduate of the Department of City and Regional Planning. My areas of expertise are affordable housing, k-12 education, and community economic development.