Silent Disco: Spatial Data Wrangling in QGIS. Preparing Data for Statistical Analysis
Online
This practical workshop teaches a crucial Geospatial Data Preparation workflow using QGIS. We will work through a publicly available dataset to demonstrate how to enrich spatial data for statistical analysis. You will learn essential QGIS techniques, including performing non-spatial joins (combining CSV tables with shapefiles), conducting spatial joins (counting features within polygons), and calculating proximity variables (distance to the nearest feature). By the end, you will produce a single, clean statistical table that is ready for analysis in external software like R, Python.
The workshop will take place via Microsoft Teams in a ‘Silent Disco’ format. Participants will work on the tutorial at their own pace. The facilitator will be available via Teams Chat to reply to any questions that arise during the event, and to help with installation, troubleshooting, or other issues.
To attend this course, you will have to join the associated Microsoft Teams group. The link to join the group will be sent to attendees before the course start date, so please make sure to do so in advance.
This course will be taught by Ki Tong.
After taking part in this event, you may decide that you need some further help in applying what you have learnt to your research. If so, you can book a Data Surgery meeting with one of our training fellows.
More details about Data Surgeries.
Those who have registered to take part will receive an email with full details on how to get ready for this course.
If you’re new to this training event format, or to CDCS training events in general, read more on what to expect from CDCS training. Here you will also find details of our cancellation and no-show policy, which applies to this event.
Level
This is a beginner-friendly course. No previous knowledge of the topic is required/expected, and the trainer will cover the basics of the method. Some familiarity with GIS and working with QGIS would be beneficial to follow the content, but is not mandatory.
Learning Outcomes
- Successfully integrate data using both non-spatial table joins and advanced Spatial Join tools (counting features and extracting nearest neighbour attributes).
- Apply Proximity Analysis tools to calculate the distance to a key spatial feature, creating a crucial statistical variable.
Prepare, clean, and export a final, consolidated statistical table from QGIS into a CSV format after using simple syntax in the Field Calculator to create new fields.
Skills
- QGIS Proximity Tools (e.g., Distance to Nearest Hub).
- QGIS Table Joins (non-spatial and Spatial Join for aggregation).
- Data Management (Field Calculator for data manipulation and exporting clean CSV files).
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