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Geospatial Data in Python with GeoPandas Parts 1-2

February 22 @ 12:00 PM - 3:00 PM

Online via Zoom,

See organizers’ website for details

Geospatial data are an important component of social science and humanities data visualization and analysis. This workshop will introduce basic methods for working with geospatial data in Python using GeoPandas, a relatively new Python library for working with geospatial data that has matured and stabilized in the last few years. In the workshop we will import geospatial data stored in shapefiles and CSV files into geopandas objects. We will explore methods for subsetting and spatial reshaping these objects. We will use geopandas methods for defining and transforming coordinate reference systems. Participants will also join tabular data to geospatial data and create maps based on the data values.

Knowledge Requirements: Basic knowledge of geospatial data is expected. Python experience equivalent to the D-Lab Python Fundamentals workshop series is required to follow along with the tutorial.

Technology Requirements: Bring a laptop with Python 3 and the following Python packages installed: pandas, numpy, matplotlib, geopandas, shapely and folium. If you do not have these installed you can follow along in the Google Collaboratory online python environment.

Details

Date:
February 22
Time:
12:00 PM - 3:00 PM
Event Category:
Website:
https://dlab.berkeley.edu/training/geospatial-data-python-geopandas-parts-1-2

Organizer

D-Lab

Venue

Online via Zoom