Metadata-Version: 2.1
Name: pandas-stubs
Version: 1.4.3.220724
Summary: Type annotations for pandas
Home-page: https://pandas.pydata.org
License: BSD-3-Clause
Author: The Pandas Development Team
Author-email: pandas-dev@python.org
Requires-Python: >=3.8,<3.11
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering
Requires-Dist: types-pytz (>=2022.1.1)
Project-URL: Bug Tracker, https://github.com/pandas-dev/pandas-stubs/issues
Project-URL: Documentation, https://pandas.pydata.org/pandas-docs/stable
Project-URL: Repository, https://github.com/pandas-dev/pandas-stubs
Project-URL: Source Code, https://github.com/pandas-dev/pandas-stubs
Description-Content-Type: text/markdown

# pandas-stubs: Public type stubs for pandas

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## What is it?

These are public type stubs for [**pandas**](http://pandas.pydata.org/), following the
convention of providing stubs in a separate package, as specified in [PEP 561](https://peps.python.org/pep-0561/#stub-only-packages).  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](http://mypy-lang.org/) and [pyright](https://github.com/microsoft/pyright#readme) and are currently shipped with the Visual Studio Code extension
[pylance](https://github.com/microsoft/pylance-release#readme).

## Usage

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

```python
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:

```sh
mypy round.py
```

we get the following error message:

```text
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:

```sh
pyright round.py
```

you get the following error message:

```text
 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](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.round.html)
we can fix the code:

```python
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)](https://pypi.org/project/pandas-stubs) and on [conda-forge](https://conda-forge.org/).

```sh
# conda
conda install pandas-stubs
```

```sh
# or PyPI
pip install pandas-stubs
```

## Dependencies

- [pandas: powerful Python data analysis toolkit](https://pandas.pydata.org/)
- [typing-extensions >= 4.2.0 - supporting the latest typing extensions](https://github.com/python/typing_extensions#readme)

## Installation from sources

- Make sure you have `python >= 3.8` installed.
- Install poetry

```sh
# conda
conda install poetry
```

```sh
# or PyPI
pip install poetry
```

- Install the project dependencies

```sh
poetry update -vvv
```

- Build and install the distribution

```sh
poetry run poe build_dist
poetry run poe install_dist
```

## License

[BSD 3](LICENSE)

## 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](https://github.com/microsoft/python-type-stubs)
together with the [VirtusLabs pandas_stubs repository](https://github.com/VirtusLab/pandas-stubs).

These stubs were initially forked from the Microsoft project <https://github.com/microsoft/python-type-stubs> as of [this commit](https://github.com/microsoft/python-type-stubs/tree/6b800063bde687cd1846122431e2a729a9de625a).

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](https://github.com/pandas-dev/pandas-stubs/issues).  

## Discussion and Development

Most development discussions take place on GitHub in the [pandas-stubs repository](https://github.com/pandas-dev/pandas-stubs/). Further, the [pandas-dev mailing list](https://mail.python.org/mailman/listinfo/pandas-dev) can also be used for specialized discussions or design issues, and a [Gitter channel](https://gitter.im/pydata/pandas) 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.

