Skip to main content

StatsCanPy

Unit Tests

Upload Python Package

Basic package for querying & downloading StatsCan data by table name. Saves data into a dataframe (Pandas or PySpark).

Allows for querying datasets via plain text search or table ID.

Installation

pip install statscanpy

Usage

Basic Usage

  from statscanpy import StatsCanPy

  # if isSpark==True, data returns will be in PySpark; otherwise it will return as a pandas.DataFrame
  statscan = StatsCanPy(path="/data/saved/here", isSpark=True)

Getting Table ID from Table Name

  await statscan.get_table_id_from_name("Household spending, Canada, regions and provinces")

Getting Table Data from Table Name

  await statscan.get_table_from_name("Household spending, Canada, regions and provinces")

Searching for Table(s) by String

  statscan.find_table_id_from_name("GDP", limit=15)

Further Reading

Metadata

Release files for statscanpy 1.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for statscanpy 1.1.1
File Size Uploaded Provenance Actions
statscanpy-1.1.1.tar.gz 4.4 kB Without provenance Details for statscanpy-1.1.1.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for statscanpy 1.1.1
File Interpreter ABI Platform Actions
statscanpy-1.1.1-py3-none-any.whl Python 3 none any Details for statscanpy-1.1.1-py3-none-any.whl

Total release size: 8.5 kB

Release files / statscanpy-1.1.1.tar.gz

Download URL statscanpy-1.1.1.tar.gz
Size 4.4 kB
Tags Source
SHA-256 checksum
How to use checksums
7f592353ff6bc968f82ae8041149615e60846057d014af81633c795627512d55
BLAKE2b-256 checksum
How to use checksums
a7f9fbd2b4fc39ff842b2cfd00edf4298a09d8080ffd6b4e4f5ab3f1e2f750ff
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.1 CPython/3.9.19

Release files / statscanpy-1.1.1-py3-none-any.whl

Download URL statscanpy-1.1.1-py3-none-any.whl
Size 4.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
007dcb19e90ce42fc08f07a50f6229dc53309923c53313e4ceba81eb5ec22fb3
BLAKE2b-256 checksum
How to use checksums
ed8c8f074cee2ece2fc5dfe2e11056ae0ddd1945373c55f60dacbf0ff6b0dafe
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.1 CPython/3.9.19

Security for statscanpy 1.1.1

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page