The open data portals have become a reality for a few years. However, data availability does not completely solve the challenge of their exploitation. The user still has to juggle with a wide range of portals, a lack of data normalization on them regarding data format and/or dataset structure and with short availability through time.
This training will allow participants to become aware of how to exploit such open data, thanks to the development of a tangible example: shared bike systems in two large french cities (namely, Bordeaux and Lyon). From data gathering to analyze, and even until data restitution onto a web API, this training will illustrate a whole open data exploitation pipeline.
Thanks to this training, you will develop the following skills:
- Know how to get an open dataset on a public portal
- Request a database from Python
- Do a simple statistic analysis
- Share its result through a web API
This program is indicative. It could be adapted to your specific needs.
- Data extraction from public open data portals
- Discovering Bordeaux and Lyon open data portals
- Get a simple dataset from data portals (shared bike availability)
- Put bike data in database
- In-base dataset handling wiwth psql (PostgreSQL)
- Dataset handling with Python
- Get the data automatically with a CRON job
- Statistical analysis of shared bike availability
- Data description: elementary statistics
- Feature extraction: how to create additional information
- Shared-bike station classification starting from their availability profile
- Short-term bike availability prediction
- Data visualization
- Plotting geo-referenced data in QGIS
- Build a simple web API to visualize in-base data
- Ease in Python programming language
- Knowledges in databases and SQL language
- Knowledge about most common data formats (csv, json)
- Notions about web programming (scrapping, API conception)
The next courses (Lyon or Paris):
Contact us for on-site trainings (dates are flexible to your needs).
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