Querying RDF data in Python
Zürich Statistical Office (opens new window) collects and publishes statistical information from all areas of life. That includes demographics, economy, construction, residency and politics. Corresponding datasets are published as Linked Data (opens new window).
These tutorials show how to work with Linked Data. They demonstrate how to query data published by city of Zürich. We recommend them to:
Explore datasets from Zürich Statistical Office
Retrieve data slices about demographics, real estate and economics
Visualize these data slices
If you are familiar with SPARQL, you can execute your queries here: https://ld.stadt-zuerich.ch/sparql/ (opens new window). Our tutorials show how to work with SPAQRL directly in Python.
We provide tutorials on data model, and data exploration.
Use data exploration tutorials to:
learn how to work with SPARQL in Python
find demographics, economics, or real estate data
learn about Zürich over time
Use data model tutorial if:
you want to find other datasets about Zürich
you don't know how to formulate queries to access it
Here we explain the logic behind Zürich's Linked Data model. This tutorial will guide you through the data structure. It will show you available datasets and the shape they take. You will find there queries explaining data structure, and available dimensions.
The tutorials are:
These tutorials explore available datasets. You will see how to query, preprocess and visualize Zürich datasets. You will find there queries for specific observations.
Available tutorials are:
If you want to know more about working with Linked Data, get in touch. We're happy to provide consulting services, development and support for your business.