Skip to main content

Type annotations for pandas

Project description

pandas-stubs: Public type stubs for pandas

PyPI Latest Release Conda Latest Release Package Status License Downloads Gitter Powered by NumFOCUS Code style: black Imports: isort

What is it?

These are public type stubs for pandas, following the convention of providing stubs in a separate package, as specified in PEP 561. The stubs cover the most typical use cases of pandas. In general, these stubs are narrower than what is possibly allowed by pandas, but follow a convention of suggesting best recommended practices for using pandas.

The stubs are likely incomplete in terms of covering the published API of pandas.

The stubs are tested with mypy and pyright and are currently shipped with the Visual Studio Code extension pylance.

Usage

Let’s take this example piece of code in file round.py

import pandas as pd

decimals = pd.DataFrame({'TSLA': 2, 'AMZN': 1})
prices = pd.DataFrame(data={'date': ['2021-08-13', '2021-08-07', '2021-08-21'],
                            'TSLA': [720.13, 716.22, 731.22], 'AMZN': [3316.50, 3200.50, 3100.23]})
rounded_prices = prices.round(decimals=decimals)

Mypy won't see any issues with that, but after installing pandas-stubs and running it again:

mypy round.py

we get the following error message:

round.py:6: error: Argument "decimals" to "round" of "DataFrame" has incompatible type "DataFrame"; expected "Union[int, Dict[Any, Any], Series[Any]]"  [arg-type]
Found 1 error in 1 file (checked 1 source file)

And, if you use pyright:

pyright round.py

you get the following error message:

 round.py:6:40 - error: Argument of type "DataFrame" cannot be assigned to parameter "decimals" of type "int | Dict[Unknown, Unknown] | Series[Unknown]" in function "round"
    Type "DataFrame" cannot be assigned to type "int | Dict[Unknown, Unknown] | Series[Unknown]"
      "DataFrame" is incompatible with "int"
      "DataFrame" is incompatible with "Dict[Unknown, Unknown]"
      "DataFrame" is incompatible with "Series[Unknown]" (reportGeneralTypeIssues)

And after confirming with the docs we can fix the code:

decimals = pd.Series({'TSLA': 2, 'AMZN': 1})

Version Numbering Convention

The version number x.y.z.yymmdd corresponds to a test done with pandas version x.y.z, with the stubs released on the date mm/yy/dd. It is anticipated that the stubs will be released more frequently than pandas as the stubs are expected to evolve due to more public visibility.

Where to get it

The source code is currently hosted on GitHub at: https://github.com/pandas-dev/pandas-stubs

Binary installers for the latest released version are available at the Python Package Index (PyPI) and on conda-forge.

# conda
conda install pandas-stubs
# or PyPI
pip install pandas-stubs

Dependencies

Installation from sources

  • Make sure you have python >= 3.8 installed.
  • Install poetry
# conda
conda install poetry
# or PyPI
pip install poetry
  • Install the project dependencies
poetry update -vvv
  • Build and install the distribution
poetry run poe build_dist
poetry run poe install_dist

License

BSD 3

Documentation

Documentation is a work-in-progress.

Background

These stubs are the result of a strategic effort lead by the core pandas team to integrate Microsoft type stub repository together with the VirtusLabs pandas_stubs repository.

These stubs were initially forked from the Microsoft project https://github.com/microsoft/python-type-stubs as of this commit.

We are indebted to Microsoft and that project for the initial set of public type stubs. We are also grateful for the original pandas-stubs project at https://github.com/VirtusLab/pandas-stubs that created the framework for testing the stubs.

Getting help

Ask questions and report issues on the pandas-stubs repository.

Discussion and Development

Most development discussions take place on GitHub in the pandas-stubs repository. Further, the pandas-dev mailing list can also be used for specialized discussions or design issues, and a Gitter channel is available for quick development related questions.

Contributing to pandas-stubs

All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. See https://github.com/pandas-dev/pandas-stubs/tree/main/docs/ for instructions.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pandas-stubs-1.4.3.220702.tar.gz (77.2 kB view details)

Uploaded Source

Built Distribution

pandas_stubs-1.4.3.220702-py3-none-any.whl (124.2 kB view details)

Uploaded Python 3

File details

Details for the file pandas-stubs-1.4.3.220702.tar.gz.

File metadata

  • Download URL: pandas-stubs-1.4.3.220702.tar.gz
  • Upload date:
  • Size: 77.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.11.3 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.64.0 CPython/3.9.12

File hashes

Hashes for pandas-stubs-1.4.3.220702.tar.gz
Algorithm Hash digest
SHA256 1a8c22f096655f25c2cf18258b2cdecd339da9bc50d251060604cb67b7958050
MD5 f5f96babf7d1a0868105a237f09cdc68
BLAKE2b-256 97be86bc167644ae74b8a604cd34e2029af9dae253294361558b146ac7ce8151

See more details on using hashes here.

Provenance

File details

Details for the file pandas_stubs-1.4.3.220702-py3-none-any.whl.

File metadata

  • Download URL: pandas_stubs-1.4.3.220702-py3-none-any.whl
  • Upload date:
  • Size: 124.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.11.3 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.64.0 CPython/3.9.12

File hashes

Hashes for pandas_stubs-1.4.3.220702-py3-none-any.whl
Algorithm Hash digest
SHA256 d58a967c8388d76feb3cee7738865e8c69aabdf9686d96dd9e9daa821ec1ceaf
MD5 4f5468f0206172e2a4dcbd4347e4baa9
BLAKE2b-256 bdeb0aa31c62ed6d81131086bfd454ff68e85fc0ab1c44b8d9b7463b9fd20267

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page