stats-can
Read StatsCan data into python, mostly pandas dataframes
Decision gist · record as of 2026-08-14
Yes, if you work with Canadian statistical data and want programmatic access without manual downloads. The package is actively maintained, has low install friction, and covers most WDS use cases. The GPL-3.0-or-later license is a consideration only if you're building proprietary software; for research, analysis, or open-source projects it poses no barrier. No known security vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later (supports current versions, <4.0).
- Statistics Canada Table/Vector IDs must be obtained from the StatCan data page.
- Low install friction with a pure-Python wheel and five common dependencies (requests, tqdm, pandas, numpy, pydantic).
License · maintenance · safety
GPL-3.0-or-later (copyleft) — GPL-3.0-or-later (copyleft): any derivative work or distribution must also be open-source under compatible terms. Suitable for internal or open-source projects but incompatible with proprietary closed-source applications.
last release 2026-04-14 (122 days) · last repo commit 2026-04-14 · 77 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 129,495 downloads/mo, #11,667 on PyPI
Alternatives
Verify before relying
pip install stats-can
import stats_can
df = stats_can.table_to_df('table_id')
# or
df = stats_can.vector_to_df(['vector_id'])- Whether all WDS endpoints are fully implemented or if some remain unsupported
- Performance characteristics when fetching large tables or many vectors
- Rate limiting or throttling behavior from the Statistics Canada API
What it is and what it does
stats-can is a Python client for Statistics Canada's Web Data Service (WDS), wrapping the official API to make it easier to fetch Canadian statistical data directly into pandas DataFrames. It implements most WDS functions and adds convenience helpers for common workflows like loading tables by ID or retrieving vectors of time-series data. The library depends on requests for HTTP calls, pandas and numpy for data handling, tqdm for progress feedback, and pydantic for validation.
The package is aimed at data analysts, researchers, and developers working with Canadian statistics who want to programmatically access StatCan data without manual downloads. It handles the API plumbing and data transformation, letting you focus on analysis rather than HTTP mechanics.
Use it for
- Download Canadian census or demographic tables into a DataFrame for analysis or visualization
- Retrieve time-series economic indicators (e.g., employment, inflation) from StatCan vectors
- Automate regular data pulls from Statistics Canada for reporting or dashboards
- Combine multiple StatCan tables in a single Python script for cross-dataset analysis
- Build data pipelines that ingest official Canadian statistics into a data warehouse
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work with Canadian statistical data and want programmatic access without manual downloads.
The package is actively maintained, has low install friction, and covers most WDS use cases. The GPL-3.0-or-later license is a consideration only if you're building proprietary software; for research, analysis, or open-source projects it poses no barrier. No known security vulnerabilities.
Install
stats-can on PyPI
Before you install
Low install friction with a pure-Python wheel and five common dependencies (requests, tqdm, pandas, numpy, pydantic). Actively maintained as of 2026-04-14 with regular commits.
Requires Python 3.10 or later (supports current versions, <4.0). Statistics Canada Table/Vector IDs must be obtained from the StatCan data page.
License in practice
GPL-3.0-or-later (copyleft): any derivative work or distribution must also be open-source under compatible terms. Suitable for internal or open-source projects but incompatible with proprietary closed-source applications.
Quickstart
pip install stats-can
import stats_can
df = stats_can.table_to_df('table_id')
# or
df = stats_can.vector_to_df(['vector_id'])Verify before relying
- Whether all WDS endpoints are fully implemented or if some remain unsupported
- Performance characteristics when fetching large tables or many vectors
- Rate limiting or throttling behavior from the Statistics Canada API
Package facts
| License | GPL-3.0-or-later copyleft |
| Python support | Supports the current Python release <4.0,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packagesrequeststqdmpandasnumpypydantic |
| Maintenance | Actively maintained 122 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 129,495 / month, #11,667 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: stats_can-3.2.3-py3-none-any.whl
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