Exploring Canadian Geospatial Data with GeoPandas in Colab Notebooks

Authors

  • Christopher Hewitt Western University, Wilfrid Laurier University

DOI:

https://doi.org/10.15353/acmla.n173.5671

Keywords:

Google Colab, Python, GeoPandas, Open Source, Statistics Canada, Cartography

Abstract

Google Colab with the GeoPandas Python package is an effective platform for GIS analysis. Following a tutorial prepared by the author, this review discusses how users can load, project, query and visualize GIS data through graphs and maps. Future directions of where this platform could be taken are also discussed. Lastly, the benefits and drawbacks of GIS analysis with Google Colab are presented.

Author Biography

Christopher Hewitt, Western University, Wilfrid Laurier University

Assistant Professor (Part Time), Western University, Research Associate, Wilfrid Laurier University

References

Arribas-Bel, D., Knaap, E., Barcelos, G., Shao, H., Gaboardi, J., Sauer, J., et al. (2020). PySAL. https://pysal.org/

Google. (n. d.). Welcome to Colaboratory - Colaboratory. https://colab.research.google.com/notebooks/intro.ipynb

Ontario Council of University Libraries (n. d.). Scholars GeoPortal. geo.scholarsportal.info

Rogerson, P. A. (2021). Spatial Statistical Methods for Geography. London: Sage.

RStudio Team. (2020). RStudio: Integrated development for R. Boston: RStudio, Inc. http://www.rstudio.com/.

University of Toronto (2010). Computing in the Humanities and Social Sciences. http://chass.toronto.edu/facilities/

Van den Bossche, J., Fleischmann, M., McBride, J., Ward, B., Wolf, L., & Richards, M. (2022). GeoPandas 0.dev+untagged. https://geopandas.org/en/stable/index.html

Van den Bossche, J., Jordahl, K., Fleischmann, M., McBride, J., Wasserman, J., Richards, M., et al. (2023, June 6). geopandas/geopandas: v0.13.2 (Version v0.13.2). Zenodo. http://doi.org/10.5281/zenodo.3946761

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Published

2024-04-01

How to Cite

Hewitt, C. (2024). Exploring Canadian Geospatial Data with GeoPandas in Colab Notebooks. Bulletin - Association of Canadian Map Libraries and Archives (ACMLA), (173), 14–17. https://doi.org/10.15353/acmla.n173.5671

Issue

Section

Geospatial Data and Software Reviews

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