Overview
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.
When it comes to accessing and downloading geospatial data, and finding creative and informative ways to map it, there are a lot of options! Part 3 of this workshop will introduce methods to downloading geospatial data using APIs and how to map them. Topics such as base maps and interactive mapping will also be covered to create visual tools that are applicable to multiple disciplines from the natural sciences to humanities. These techniques will be implemented using packages such as folium, contextily, and geopandas. Participants will be able to create meaningful visuals that combine multiple sources of data.
Prerequisites: D-Lab’s Python Fundamentals introductory series or equivalent knowledge. Basic knowledge of geospatial data is expected.
NOTE: D-Lab workshops normally start 10 minutes after the scheduled start time (“Berkeley Time”). We recommend you log on at the start time to join the waiting room where hosts will message you further information.
Type: Workshop
Keyword: Software Tools, Python, Geospatial Analysis
Training Keywords: Geospatial Data, Maps and Spatial Analysis
Primary Tool: Python
Training Learner Level: Basic Competency
Training Host: D-Lab
D-lab Facilitator: Patty Frontiera
Format Detail: Remote, hands-on, interactive
Participant Technology Requirement: Laptop, Internet connection, Zoom account
Workshop materials: https://github.com/dlab-berkeley/Geospatial-Fundamentals-in-Python
