Check the Setup
- Python 3.10 or newer
- A notebook environment such as Jupyter or Google Colab
- An internet connection
Zoning polygons, classifications, categories, districts, and CD-1 identifiers for building land-use and development-potential analysis tools.
Report a ProblemFrom Source to Product Signal
Start with one zoning classification and a small page of district polygons. Some features are less precise than survey data, and the dataset does not replace the Zoning and Development By-law.
Install the packages, then run the notebook cell.
python -m pip install pandas requests
import pandas as pd
import requests
url = "https://opendata.vancouver.ca/api/explore/v2.1/catalog/datasets/zoning-districts-and-labels/records"
response = requests.get(url, params={"limit": 100}, timeout=30)
response.raise_for_status()
zoning = pd.DataFrame(response.json()["results"])
columns = [
"object_id",
"zoning_classification",
"zoning_category",
"zoning_district",
"cd_1_number",
]
print(zoning[columns].head())
print(zoning["geom"].iloc[0]["geometry"]["type"])Test a Useful Signal
Test whether district polygons can support a neighbourhood land-use inventory.
City of Vancouver is a government source. Last verified 2026-09-03. Temporal coverage: Current zoning snapshot.