jack/dash-api
1
0
Fork 0
Code Issues 1 Pull Requests Packages Projects Releases Wiki Activity

done

Browse Source
This commit is contained in:
leene
2025-09-07 22:09:54 +02:00
parent e1b817252c
commit 2fc0d000b6
7796 changed files with 2159515 additions and 933 deletions
Download Patch File Download Diff File Expand all files Collapse all files

1
lib/python3.11/site-packages/pandas_stubs-2.3.2.250827.dist-info/INSTALLER Normal file
View File

@ -0,0 +1 @@
uv

29
lib/python3.11/site-packages/pandas_stubs-2.3.2.250827.dist-info/LICENSE Normal file
View File

@ -0,0 +1,29 @@
BSD 3-Clause License
Copyright (c) 2022, pandas
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
3. Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

203
lib/python3.11/site-packages/pandas_stubs-2.3.2.250827.dist-info/METADATA Normal file
View File

@ -0,0 +1,203 @@
Metadata-Version: 2.3
Name: pandas-stubs
Version: 2.3.2.250827
Summary: Type annotations for pandas
License: BSD-3-Clause
Author: The Pandas Development Team
Author-email: pandas-dev@python.org
Requires-Python: >=3.10
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 :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering
Classifier: Typing :: Stubs Only
Requires-Dist: numpy (>=1.23.5)
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: Homepage, https://pandas.pydata.org
Project-URL: Repository, https://github.com/pandas-dev/pandas-stubs
Description-Content-Type: text/markdown
# pandas-stubs: Public type stubs for pandas
[![PyPI Latest Release](https://img.shields.io/pypi/v/pandas-stubs.svg)](https://pypi.org/project/pandas-stubs/)
[![Conda Latest Release](https://anaconda.org/conda-forge/pandas-stubs/badges/version.svg)](https://anaconda.org/conda-forge/pandas-stubs)
[![Package Status](https://img.shields.io/pypi/status/pandas-stubs.svg)](https://pypi.org/project/pandas-stubs/)
[![License](https://img.shields.io/pypi/l/pandas-stubs.svg)](https://github.com/pandas-dev/pandas-stubs/blob/main/LICENSE)
[![Downloads](https://static.pepy.tech/personalized-badge/pandas-stubs?period=month&units=international_system&left_color=black&right_color=orange&left_text=PyPI%20downloads%20per%20month)](https://pepy.tech/project/pandas-stubs)
[![Gitter](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/pydata/pandas)
[![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://numfocus.org)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![Imports: isort](https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat&labelColor=ef8336)](https://pycqa.github.io/isort/)
[![Typing: stubs](https://img.shields.io/pypi/types/pandas-stubs)](https://pypi.org/project/pandas-stubs/)
## 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. NOTE: The current 2.0.x releases of pandas-stubs do not support all of the new features of pandas 2.0. See this [tracker](https://github.com/pandas-dev/pandas-stubs/issues/624) to understand the current compatibility with version 2.0.
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]" [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 >= 3.10` installed.
- Install poetry
```sh
# conda
conda install poetry
```
```sh
# or PyPI
pip install 'poetry>=1.2'
```
- 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 led by the core pandas team to integrate [Microsoft type stub repository](https://github.com/microsoft/python-type-stubs) with the [VirtusLabs pandas_stubs repository](https://github.com/VirtusLab/pandas-stubs).
These stubs were initially forked from the Microsoft project at <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 providing the initial set of public type stubs. We are also grateful for the original pandas-stubs project at <https://github.com/VirtusLab/pandas-stubs>, which created the framework for testing the stubs.
## Differences between type declarations in pandas and pandas-stubs
The <https://github.com/pandas-dev/pandas/> project has type declarations for some parts of pandas, both for the internal and public API's. Those type declarations are used to make sure that the pandas code is _internally_ consistent.
The <https://github.com/pandas-dev/pandas-stubs/> project provides type declarations for the pandas _public_ API. The philosophy of these stubs can be found at <https://github.com/pandas-dev/pandas-stubs/blob/main/docs/philosophy.md/>. While it would be ideal if the `pyi` files in this project would be part of the `pandas` distribution, this would require consistency between the internal type declarations and the public declarations, and the scope of a project to create that consistency is quite large. That is a long term goal. Finally, another goal is to do more frequent releases of the pandas-stubs than is done for pandas, in order to make the stubs more useful.
If issues are found with the public stubs, pull requests to correct those issues are welcome. In addition, pull requests on the pandas repository to fix the same issue are welcome there as well. However, since the goals of typing in the two projects are different (internal consistency vs. public usage), it may be a challenge to create consistent type declarations across both projects. See <https://pandas.pydata.org/docs/development/contributing_codebase.html#type-hints> for a discussion of typing standards used within the pandas code.
## 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 [Slack channel](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack) is available for quick development related questions.
There are also frequent [community meetings](https://pandas.pydata.org/docs/dev/development/community.html#community-meeting) for project maintainers open to the community as well as monthly [new contributor meetings](https://pandas.pydata.org/docs/dev/development/community.html#new-contributor-meeting) to help support new contributors.
Additional information on the communication channels can be found on the [contributor community](https://pandas.pydata.org/docs/development/community.html) page.
## 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.

186
lib/python3.11/site-packages/pandas_stubs-2.3.2.250827.dist-info/RECORD Normal file
View File

@ -0,0 +1,186 @@
pandas-stubs/__init__.pyi,sha256=hT_ag1EEVV2jK0BU4FmNu_U2KKSupglxh7EQMihWHLo,3749
pandas-stubs/_config/__init__.pyi,sha256=M3hVVpcI4IxOe3X8ojb7rBSwJJYMZqZ6QsQxoqMb110,242
pandas-stubs/_config/config.pyi,sha256=5HnxtLNtCkwrT81O_jbruoAHu87g1IOhcljulneedn8,4310
pandas-stubs/_libs/__init__.pyi,sha256=uIGa2l-74ZCZsyVXYKyFG82ElYR83LFZ8irjKcFl-B8,285
pandas-stubs/_libs/indexing.pyi,sha256=Wkc4p1QF5hje_R0A6Wuohlkw0pM9uB5v88xPXEfe0h8,132
pandas-stubs/_libs/interval.pyi,sha256=Yv7to_zuHhczruqAW9ub3aFQWVS3_DVVoFpwjxCR3pk,8476
pandas-stubs/_libs/json.pyi,sha256=NnxDbShwkcklhOE2Pvu3wdfu8Dudz4ORG_uFUSGO0qY,130
pandas-stubs/_libs/lib.pyi,sha256=PYawDhx2mPlVUjBu1qKe7b9M1-AzFDM2VHMd6dowDlQ,806
pandas-stubs/_libs/missing.pyi,sha256=dS3SwbcV-0VGKvIarntXC8e1DVOrD0eRoykDX1Qe_8Y,1893
pandas-stubs/_libs/properties.pyi,sha256=PDK-T2SwH0pINKLrXbvpniG2xyVVIxURaG7_E_EoKJ8,599
pandas-stubs/_libs/sparse.pyi,sha256=3Hhu3OSulidZf89Q4QYOboL7n3kGsD2uagzO4c88g7A,91
pandas-stubs/_libs/tslibs/__init__.pyi,sha256=eQ7p1VtoczZ68-bhDQwD7SUb2I4yAxYtlkDxpeQLKyw,666
pandas-stubs/_libs/tslibs/base.pyi,sha256=oyNW_3SZ9QeHkaELcQSoXU13z591Nqm6tvxTP9YGVo0,65
pandas-stubs/_libs/tslibs/conversion.pyi,sha256=p4GXyC31YWA8JnTr8TUU4jzK2yeeTNYXoSHjGoKH8uU,45
pandas-stubs/_libs/tslibs/nattype.pyi,sha256=8_RBlFl1FlCTrLxLEV2h4rJJXrUP1CWa86YKFbYQycY,4562
pandas-stubs/_libs/tslibs/np_datetime.pyi,sha256=n1inLsD2QK9cMO47g-N0KDd90zWdDy83OnO5lrkSKDU,89
pandas-stubs/_libs/tslibs/offsets.pyi,sha256=CavfXR2LJlgVmwVyxyYUvYtBWCZSzzNLzDOIyZRXezk,8082
pandas-stubs/_libs/tslibs/parsing.pyi,sha256=n184K_KvA9II0UDRucg7Gs4eSFPIKU0Qpsyb84hEp6c,89
pandas-stubs/_libs/tslibs/period.pyi,sha256=yGTg4Gg9XWznH-9WifeRlJMY2LypjDhBUg1O4pfsWxc,7516
pandas-stubs/_libs/tslibs/timedeltas.pyi,sha256=mwueRYMosNtXm91O8S4WqVHc5VvNQ-uvFsHyt08acAA,15341
pandas-stubs/_libs/tslibs/timestamps.pyi,sha256=JiMUANqc9GLxU3BxBb2xJKY7rn3E1SJ_uT61wU3RcBI,12823
pandas-stubs/_libs/window/__init__.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/_testing/__init__.pyi,sha256=LUdzs5UKJmE2YpFaBRjQUaVbRNFu-KFHewrmV7Pzxj8,5782
pandas-stubs/_typing.pyi,sha256=9BAIjYXLjjcrMRowzbsDs0tjFi17-yKGAeLB7HgukhY,33373
pandas-stubs/_version.pyi,sha256=wbgf9CRK30Pl2GSBcD8hQRkwMWORUDzxL9T8W4K_gGI,97
pandas-stubs/api/__init__.pyi,sha256=Yy4c1QLDoGulXMAR5zPOsP86bV9maHDpv_utY6XDH78,164
pandas-stubs/api/extensions/__init__.pyi,sha256=Q-QrCzb7h0ZgspNwnZdWehMQchbvO3Te0k4hEgaOl2E,601
pandas-stubs/api/indexers/__init__.pyi,sha256=nS32m1m1Y3K2GsrpsklQvH_wtCnTYCZwXLqZYDuK1nA,283
pandas-stubs/api/interchange/__init__.pyi,sha256=7cPmI3jy6or0-0Lg3kvRRq1NiqSlKAZGWCLTWEEcB8Q,164
pandas-stubs/api/types/__init__.pyi,sha256=cGfZzApbzuvrJQELEGspR4NxY5XPhb1C2PhFTeICxqw,1692
pandas-stubs/api/typing/__init__.pyi,sha256=echDAFPWzbT0SXbhbMnOMzUgLLelc5_cn6_a1SVY_AI,1220
pandas-stubs/arrays/__init__.pyi,sha256=67_Mk9wf22D9QaRz7XZ_WD9ku7wJY1WMSA6ZCRuj3Z4,373
pandas-stubs/core/__init__.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/core/accessor.pyi,sha256=w7wksWHrkFnxarvuuiqRBSaGm2Eo21v_p1urIUf8lwc,320
pandas-stubs/core/algorithms.pyi,sha256=1ibK9cML9-y8xikNC8jp-Be5QzmQHt2hKghR0NsHP8o,2090
pandas-stubs/core/api.pyi,sha256=VP-Xs34k_mXqxfKdSrDr6OEw5kKA-RJGHWd5ZG7BU8c,2680
pandas-stubs/core/arraylike.pyi,sha256=OLiuhLIgk8RLS2zbEITHirf122t28SvgFilKpBJ-vX4,1929
pandas-stubs/core/arrays/__init__.pyi,sha256=Ovoau1NLbOYltbN_hxOlQA9j4EmhqqU6UhaUcQnO3Uo,878
pandas-stubs/core/arrays/arrow/dtype.pyi,sha256=yTdibSMx2rmCIyuikX5qc5Wy3w2pBqRyvvK14AW2mjA,321
pandas-stubs/core/arrays/base.pyi,sha256=sgiLlYQQy-oLg02g11QmaVoGBSXaSSyRhtlIT4jzDHc,2566
pandas-stubs/core/arrays/boolean.pyi,sha256=5V1pv54bwov584c3gmYBQeoVIb3OXZJKasWMaui-viI,898
pandas-stubs/core/arrays/categorical.pyi,sha256=DZz-N8HR9UI7zbLrZvKIfoSxs9SSafIdC-GQbKgcZfU,5519
pandas-stubs/core/arrays/datetimelike.pyi,sha256=7Mc8xeuPmSjnTPVr4_a3DBtggGpn0bgXXVjKQzJD4vs,3357
pandas-stubs/core/arrays/datetimes.pyi,sha256=CqIlAw008d0hvS4LX2E39pZ5QWedc__dIFwdnQuObCI,2318
pandas-stubs/core/arrays/floating.pyi,sha256=1KM9z9r009mksYlXm6dqohhA4PygGg2zRcCtkM3Nn7A,133
pandas-stubs/core/arrays/integer.pyi,sha256=9_BAqYX1iGfUKopB6gEwSz5JPo4_PXPsv4ozZODO3xc,1061
pandas-stubs/core/arrays/interval.pyi,sha256=T_SHLjmzKoiqQ4D0dvfdMIW6zS4sJIVycgWZa7tbpbc,3130
pandas-stubs/core/arrays/masked.pyi,sha256=QKfD0d-z6ccmkDFDa1785ZPxaGt0tpHenB7qf6BZIq4,1072
pandas-stubs/core/arrays/numeric.pyi,sha256=eX0wsYnihkRg2bfHpip7Kc_7a_s94db_BIabxRg1EGA,99
pandas-stubs/core/arrays/numpy_.pyi,sha256=nDWCXkB6OIs5rYnhkm_5bPCNxeSBva1R2PVZFAOh6v8,513
pandas-stubs/core/arrays/period.pyi,sha256=5d30Wo0a9ZsjahcLX5ziXcbxFSJXnbxfs0voPjKb9R8,1345
pandas-stubs/core/arrays/sparse/__init__.pyi,sha256=_mA7bnyFne-O-Wl_I1Ry18bGpETInr-eCbrl6_PdcVo,285
pandas-stubs/core/arrays/sparse/accessor.pyi,sha256=4iV0z6bEmIC3jXOJ5suO6j3YQcFbEapRkfWS6kQ0HjM,654
pandas-stubs/core/arrays/sparse/array.pyi,sha256=uZHdqeXLDkFhFKSz4_33DMYrjQjU8fIdiEgP_yIp6ZE,2276
pandas-stubs/core/arrays/sparse/dtype.pyi,sha256=iKuzugk6tll8nUhbJuj2KKtYcWlwZQf71ZlN9TAhqYM,448
pandas-stubs/core/arrays/string_.pyi,sha256=LmyXDoLgydajvLdeVlPRtIBrnVSjhfeaTSCl8QDyxyU,719
pandas-stubs/core/arrays/timedeltas.pyi,sha256=A1rl5LsDF_c7hPMIDlGrWwaeGeDnBwLjgS-cUE2sVuY,1755
pandas-stubs/core/base.pyi,sha256=HYuaYVtnhxP7gDucdIVXQ3dlAWr-8y6KlzELp4uiu-4,3760
pandas-stubs/core/computation/__init__.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/core/computation/api.pyi,sha256=QfpeM8ecu0zSwcgCgoZkzHTdOeQN7TFam5BQlFydyrc,54
pandas-stubs/core/computation/engines.pyi,sha256=m2OVCBGklTP9Mxp__ZcPXlWbAvWnQOH91Ost2wxl6G8,438
pandas-stubs/core/computation/eval.pyi,sha256=8Xaiz-96XebeRyfhEe6U8C5xEnSRoXVH32PFt8TwdV8,676
pandas-stubs/core/computation/expr.pyi,sha256=_i4PQBAO6ABOmCS_1bfFucXWR3mTKf0EGDD_QvgilLA,2032
pandas-stubs/core/computation/ops.pyi,sha256=RtJUfWlmPWD4wZsiRmMl8UP-RTSv_lXedSRwVbhQfPs,2309
pandas-stubs/core/computation/pytables.pyi,sha256=Jy3EsfOeEu3r-1mt5QC_vjqftEnTuhm1PtoKM4I-onI,3026
pandas-stubs/core/computation/scope.pyi,sha256=lUY0rSesK8Vw6E6DB_bSvIzP5Ry6qq0ozGVHd9wRxr0,543
pandas-stubs/core/config_init.pyi,sha256=ZiBQNqel1PJ4oTgRUPy-fhXqb3yupZey1-IP7S4N9TY,1436
pandas-stubs/core/construction.pyi,sha256=a3zbgwBu0ylQB3U-14-gcjWYnlrWAJ1-fNvkH1roj7c,320
pandas-stubs/core/dtypes/__init__.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/core/dtypes/api.pyi,sha256=uhx_T-HH6HljpFrVNdLrqFlZKnDQwbhdgwjglbxfjEs,1358
pandas-stubs/core/dtypes/base.pyi,sha256=HVOUVIbigZejdWzeFqrT5r60zVNjMpD2s06yoIJRSas,1017
pandas-stubs/core/dtypes/cast.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/core/dtypes/common.pyi,sha256=sEdrYLehFpUWIXQ11uLILsnOhi7bocgh7_mTfB0jwCs,2008
pandas-stubs/core/dtypes/concat.pyi,sha256=FNQI-XDA6RfuOT9WByhodcn5GEqjQCWX1XxHJAKtoT0,331
pandas-stubs/core/dtypes/dtypes.pyi,sha256=RrT-NAq7oPBM2zSPIY4UHZ23ZGpbLM0oygPe-sOFIp4,1747
pandas-stubs/core/dtypes/generic.pyi,sha256=NlO7NPa8RxfU6ZcUGkzPoClIuICZNnnQudmH05FMnOs,207
pandas-stubs/core/dtypes/inference.pyi,sha256=LDJa90P9tzoYnLhUUISZQp7HHwtOwKfSM4ZZ2hTJhps,534
pandas-stubs/core/dtypes/missing.pyi,sha256=dCI_ykcFy6sB5v6VFFsRLD0e9uOscnYlBMKLxPOxLac,1418
pandas-stubs/core/frame.pyi,sha256=wA_O4cNvcG_vppFrLHrfP_18fMHatSxwHPYidxtCZRU,80156
pandas-stubs/core/generic.pyi,sha256=9eVeekKCeW_6SshPQt9rLgdu3nUyiGXTX1wpA0ICNJg,13288
pandas-stubs/core/groupby/__init__.pyi,sha256=UjcLlmy8DHX5As_Rw-S3y88bEYbpqnX6vZFCADJLYwY,387
pandas-stubs/core/groupby/base.pyi,sha256=6bwVfZCTDXvM0PEEkqsL8Erv1aUdkkjrBTX2zZ24TAk,1031
pandas-stubs/core/groupby/categorical.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/core/groupby/generic.pyi,sha256=05Cur2GrUG7PyiiUPrO6EeQVB7t5FbhayGHZWH2e6nw,14138
pandas-stubs/core/groupby/groupby.pyi,sha256=7yxDQ8xp_62ECUq67rIus5TdksLJg7WsUZX5y2BNb_U,12011
pandas-stubs/core/groupby/grouper.pyi,sha256=mZlx-ESLcbW4vYWhXWfDgNjmKRN1riQsnmo3n-D8euk,1859
pandas-stubs/core/groupby/indexing.pyi,sha256=JrZ-xiEYQ9aMDcefzAnghUrLlTl6XV1NEnQ1TEvBg-0,805
pandas-stubs/core/groupby/ops.pyi,sha256=zJbbw3B1JNHLwJN55Sf1q0Pqn1TdWi2z_aS65v8gBVs,2777
pandas-stubs/core/indexers.pyi,sha256=gBAcxtnpm7Q8LettPKVMIf27oY-QFrbgqYSN_DxrsOU,1239
pandas-stubs/core/indexes/__init__.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/core/indexes/accessors.pyi,sha256=dDhPC_IByFE9iBztAnZHNds-b-PpK7SwUQYuRP6V_e4,13298
pandas-stubs/core/indexes/api.pyi,sha256=LauH0wsqf-7ETazueqLCwhK49M8IPfsR5gGBfRYiim4,551
pandas-stubs/core/indexes/base.pyi,sha256=JAUa-fMiXVj3JzelbAnsOzAv3viHAfM_93bmhjrtFOQ,15978
pandas-stubs/core/indexes/category.pyi,sha256=yft63au1ka1bpNdTPeuYYXfM0N5tNy2K8eEe7hPzPYc,1503
pandas-stubs/core/indexes/datetimelike.pyi,sha256=9SUgf4z_jMXPWpjViIdY8taHqUVpZYXs6vdBkHRAa5I,1323
pandas-stubs/core/indexes/datetimes.pyi,sha256=MFol80xd19S3ktyQQJgRIdDBo_X0E52ojUZQoHbISxk,5278
pandas-stubs/core/indexes/extension.pyi,sha256=WE0SJEMxPLdOkbEo_FucH0qpmVGDLz_wqaoeKJPIg5Q,185
pandas-stubs/core/indexes/frozen.pyi,sha256=u1LZmVY_xCV61lrzV6zkXMRqS3OZtCbonpUipNVrIm8,419
pandas-stubs/core/indexes/interval.pyi,sha256=D1ElUfOmooYRed5msLevkQLaKT_vYohti6u70t6RkSM,11962
pandas-stubs/core/indexes/multi.pyi,sha256=h_UT2LrpBSS2fuzvrbY5Cws7e_i0d8otmgxBgwMlQLo,5354
pandas-stubs/core/indexes/period.pyi,sha256=mk4t0yDe07sMgd7y764wpnjIDkFKf2zM8VckJPNA0Ck,2441
pandas-stubs/core/indexes/range.pyi,sha256=3SUq0VlwfTqrQSPTZvtWg3HxFnDawjYldomSX-UI7dc,2694
pandas-stubs/core/indexes/timedeltas.pyi,sha256=9lE1IjrM3-Sq02oC1Lq_kDJ088EXP_XeeRJeWpio7qQ,4265
pandas-stubs/core/indexing.pyi,sha256=5cFa0X0D6GYTFNF-dQsW8c2q7k1szR3Jt9897qGA--M,1490
pandas-stubs/core/interchange/__init__.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/core/interchange/dataframe_protocol.pyi,sha256=yPhtq_dFIcVmAh5yTxVxWaW1VVlY0UDZHqJFLNNjXbE,3417
pandas-stubs/core/interchange/from_dataframe.pyi,sha256=2vkFxBm_i4mvaZPs6LlXo9s-CcqhJw7YuoB04DXMzq4,93
pandas-stubs/core/ops/__init__.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/core/ops/docstrings.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/core/resample.pyi,sha256=jIlFj30dPpDNaWtUGuMWnG-iuZ_YvIfb2X7UlOKPEjk,6518
pandas-stubs/core/reshape/__init__.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/core/reshape/api.pyi,sha256=8lX_Gb9I2kucIYgJBf6CnMYSCNAf8o_hW8CuGDQtD8o,633
pandas-stubs/core/reshape/concat.pyi,sha256=q3CjAb89lxZblXgRK2kZAssv0YLXtKuKGcQvbCHyrLU,5597
pandas-stubs/core/reshape/encoding.pyi,sha256=aXQbV8SW-prjZ7UiEJPXCuHHloPUSwXFmVLFZFTRSe0,700
pandas-stubs/core/reshape/melt.pyi,sha256=1cjevvh69WvYbTNq9wSSWa6rRa0UlfWBPnmDM9xTKGI,764
pandas-stubs/core/reshape/merge.pyi,sha256=DpRVogidqQlehZ-Ler_agGlN_db1N_kOswdz343YKfw,2827
pandas-stubs/core/reshape/pivot.pyi,sha256=x08v8NO7cmTBBw90NZzTAQHLCwmcyTr5-UfltszK8nU,4235
pandas-stubs/core/reshape/tile.pyi,sha256=Lq1lKmEu72w-lS6A7ZwK8AGrEqgX2hMZHjfuqIiqv4I,7968
pandas-stubs/core/reshape/util.pyi,sha256=-TQWxkkJrq35T5m8B-3VRo-S_6ivg70n7owUKdJ1_1o,30
pandas-stubs/core/series.pyi,sha256=oHEbxwwWkcQ2y3FtAOL0hI6uHYWu-QauGV1S29KOBEI,119677
pandas-stubs/core/sparse/__init__.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/core/strings/__init__.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/core/strings/accessor.pyi,sha256=zbZKboRyf0iSiV1itLjHWuiUoE63WKrkMeJxmHqEWWg,8457
pandas-stubs/core/tools/__init__.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/core/tools/datetimes.pyi,sha256=m2j9KXnv11VonsZDzdhT6KzHwNPmrPcouBvoTokzct8,3147
pandas-stubs/core/tools/numeric.pyi,sha256=JDvEjr187OI-NmGu-cY8zk-KIHkQx6FPEwU0QNk6zVs,978
pandas-stubs/core/tools/timedeltas.pyi,sha256=2ZScOEH6mNjCRfpK6Pq4U0eYLDdPXsyKom5fUmpzB9A,1094
pandas-stubs/core/util/__init__.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/core/util/hashing.pyi,sha256=V7i8ccnUlViDvih5pBs0tYel0a_B6kERnuc6SOeqrYo,535
pandas-stubs/core/window/__init__.pyi,sha256=hxMkJsmjetBCcwub68dHFoPD2tbH5GrPBN3yTi-F2p8,420
pandas-stubs/core/window/ewm.pyi,sha256=hReD_7Bu68WXilQfdwBgmaS-7321IT0i29JyMMdqQkI,2164
pandas-stubs/core/window/expanding.pyi,sha256=V-MPFyO9G0_98C_ayfOnL6Zg3hnN0He0W_My2h5Zd8k,278
pandas-stubs/core/window/rolling.pyi,sha256=iKfqoeuWV0OktWredzL0KMbeeoM-syIFFb7IPkrQBKE,5002
pandas-stubs/errors/__init__.pyi,sha256=1H88fC4UO9-El1WoDK_dU1MsPpwii50g1XiP7q5HqvQ,1808
pandas-stubs/io/__init__.pyi,sha256=XToGdOdZw-HIbXVOnaElNS-mSDXSqZcluJdXA3kjpW4,93
pandas-stubs/io/api.pyi,sha256=AVlXvvKbQTU2wEXIDxiWqfsdSPXNyLNoLRF8GOKioJU,1137
pandas-stubs/io/clipboard/__init__.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/io/clipboards.pyi,sha256=e7C_D6L6TIST8tC_HEto-_KdHQrreeTc_qX3g9qUk6E,6848
pandas-stubs/io/excel/__init__.pyi,sha256=ww6I7ddRYlFAR2VmD7XZnAPwcJRJWs6xuIWzPq_vZSo,128
pandas-stubs/io/excel/_base.pyi,sha256=G9s2QrsZYApVd5WKNBSX-NC8uw63Xz_NAKSQvKKCHR0,11336
pandas-stubs/io/feather_format.pyi,sha256=9aJBTLhn5mZdu56pfJCNg-IY3x8E9RrV9H4-POs_v6I,480
pandas-stubs/io/formats/__init__.pyi,sha256=JeiOuQ3jaG2fJtw9_zaNf8yuQGtaUHRRN72ZGg2akGI,46
pandas-stubs/io/formats/css.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/io/formats/format.pyi,sha256=l-rz36LtVOQWgWA-jtRT72kzagcFvTbHGqlXmdObSKE,338
pandas-stubs/io/formats/style.pyi,sha256=LtlPpYZ4TwUTNUMMXQd00kckfQjLnWLqlKkaUK0CzqE,12257
pandas-stubs/io/formats/style_render.pyi,sha256=I0GLj5pZMKiBycpytHc5gKehEnJFpl-gYpOJaoKK7X8,2444
pandas-stubs/io/html.pyi,sha256=mlLqat_YkLQOxBTrtxrfKb-n-NPAm3hUXRIBB7UKURM,1662
pandas-stubs/io/json/__init__.pyi,sha256=CfdAxhQxhJhA3WFrDgp3t2Pu8v-KZUVNhe7IHc5Riuc,280
pandas-stubs/io/json/_json.pyi,sha256=fI3Imdk5CZ2BPHQcvVIV3qva4f_RjEm1G0NF4yLZinw,8044
pandas-stubs/io/json/_normalize.pyi,sha256=N-ZfFfEPWuk5TgaxjjRYxStx4XZ5r5UFJ6KbiU7o0vk,412
pandas-stubs/io/json/_table_schema.pyi,sha256=KVuqEaGupNE0uNzCNppQoObn7dz9TpMhsKD974YrIik,288
pandas-stubs/io/orc.pyi,sha256=QptqGQ2XNDoFDMVerr3vWmC-EbEFZGDt5HVEk-jvHuE,583
pandas-stubs/io/parquet.pyi,sha256=YY8avUCijJx6D5EoeDcpR5AzzeADrfxHbCFGYLEtImI,550
pandas-stubs/io/parsers.pyi,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/io/parsers/__init__.pyi,sha256=-SYgeIA_uI7qXWONXuH8DKcvw3wF0t4Bz0sIafdbHf0,168
pandas-stubs/io/parsers/readers.pyi,sha256=muni2fWQUCpIxKBOxMXrg6_-NaMPEUDgGmMNoAV-znk,17078
pandas-stubs/io/pickle.pyi,sha256=UAxyPnQZhIF5fNS-bimXAw0aDvwHoGESVdQ1Ykc0rVc,325
pandas-stubs/io/pytables.pyi,sha256=zwb7hUJWuLRpEjPa_BZiYwBtpiG_FF0j4pyhsHfqyH0,6697
pandas-stubs/io/sas/__init__.pyi,sha256=b6xHfA4SXF7FTehImsIZ6_gARL1f5ORMazw8im7ylFY,58
pandas-stubs/io/sas/sas7bdat.pyi,sha256=BN1NxYCiznV1mDw602-Aqd7JYITduTlanKmcvSKcPB8,256
pandas-stubs/io/sas/sas_xport.pyi,sha256=ydEc_YBS64Q0lryf33Yqr2WbP2d_2_Lxd8rJV2W7BEA,250
pandas-stubs/io/sas/sasreader.pyi,sha256=luybi4PPq4LK0UedFrFQd0EwgE7uS6MBsbRav_lcke4,2976
pandas-stubs/io/spss.pyi,sha256=tPN_-2WYux748R-5NUND3XpYcnVdoK06rifGeboZRPY,394
pandas-stubs/io/sql.pyi,sha256=P6tDQ94fpoo__bqMPnmxYXsM0ipTbu3Nv3ezsT9N4lg,6128
pandas-stubs/io/stata.pyi,sha256=wHLHSzKzbBJzgHH-tbJODe5M_DcMjaHsczmObpgQg3Q,3846
pandas-stubs/io/xml.pyi,sha256=bq5-Cy5Y1a-z7sdISYnbIJt0reF5hnYaaDtT0YmO_dY,1144
pandas-stubs/plotting/__init__.pyi,sha256=Wy4E1wQokXUxVk4diN9pg0FWZaJYTz9FEvaMooppd-o,587
pandas-stubs/plotting/_core.pyi,sha256=beOLl4s4vmKn08KUt9Wv7wjbSyC3iDY1AAISpu8_wx0,12829
pandas-stubs/plotting/_misc.pyi,sha256=FxoYoKIRx0gHJunYn6yA3ar9Pj_49h8fYXlex_eIWWg,2387
pandas-stubs/py.typed,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas-stubs/testing.pyi,sha256=B-CYwNW09FL5sH7F2iwt_gzUUkkbXT0WrySh_TV67oI,368
pandas-stubs/tseries/__init__.pyi,sha256=cW0h2NdP0r4f-l3XfT2HhHJYND3DqAXMlVpAA1BTGdk,91
pandas-stubs/tseries/api.pyi,sha256=bCxFxPQ3dvz2-9dg7HYLyb7PKbzOGaYU2vSdrtHQcp4,64
pandas-stubs/tseries/frequencies.pyi,sha256=ixbNvEoHU7bx7pL1qA1C5IOUSOhaAyVv8o0G5O8-gJQ,443
pandas-stubs/tseries/holiday.pyi,sha256=IAwkAt4-cc3jGAvXNhQncMo64zeeT-pR9J1k9YsOBhA,4068
pandas-stubs/tseries/offsets.pyi,sha256=R8s000rv9ze7rNUuD6xN2mZrJg8etybgbZM7i-JGe6A,1312
pandas-stubs/util/__init__.pyi,sha256=eCNBKiJLOPwFZHo3sZqsK9l5AESW5IQ3jWaE1bMrLe8,121
pandas-stubs/util/_decorators.pyi,sha256=yGGvceTuT6g7i7qmddthOJTTBmJa9Wxgbok-sKVp7uY,70
pandas-stubs/util/_print_versions.pyi,sha256=jyt2W-sdntUfnlhwM82HT6Q9J2P0ydR-OWppqQDJ0HQ,55
pandas-stubs/util/version/__init__.pyi,sha256=U_9zwmqvc1-darOoXCqIaSP7vHEAkQH6b3utRwL5jSs,1899
pandas_stubs-2.3.2.250827.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2
pandas_stubs-2.3.2.250827.dist-info/LICENSE,sha256=Q3QAwxzl_ZgK6K31JiqY0iLWupIWuFMA_kWfXnGqa98,1514
pandas_stubs-2.3.2.250827.dist-info/METADATA,sha256=b7PumoX8Oyom4CTaLTbIZZ4KAtS9LWhmjkwZXictupU,10190
pandas_stubs-2.3.2.250827.dist-info/RECORD,,
pandas_stubs-2.3.2.250827.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pandas_stubs-2.3.2.250827.dist-info/WHEEL,sha256=b4K_helf-jlQoXBBETfwnf4B04YC67LOev0jo4fX5m8,88

0
lib/python3.11/site-packages/pandas_stubs-2.3.2.250827.dist-info/REQUESTED Normal file
View File

4
lib/python3.11/site-packages/pandas_stubs-2.3.2.250827.dist-info/WHEEL Normal file
View File

@ -0,0 +1,4 @@
Wheel-Version: 1.0
Generator: poetry-core 2.1.3
Root-Is-Purelib: true
Tag: py3-none-any