semvec/pypi-packages huggingface dataset:
recorpy 0.1.7
ReCorPy is a small package to reorder correlation matrices from dataframes for better visualizations
Requires Python: >=3.7,<4.0
Keywords: correlation matrix,visualization,clustering


<p align="center">
  <img src="https://raw.githubusercontent.com/thebooort/ReCorPy/main/assets/logo.png">
</p>
<h2 align="center">ReCorPy</h2>

> A python's package for reordering/clustering correlation matrices

[![DOI](https://zenodo.org/badge/506917975.svg)](https://zenodo.org/badge/latestdoi/506917975)
[![Documentation Status](https://readthedocs.org/projects/recorpy/badge/?version=latest)](https://recorpy.readthedocs.io/en/latest/?badge=latest)
[![PyPI Version][pypi-image]][pypi-url]
[![Build Status][build-image]][build-url]
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<a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>

`recorpy` reorder correlation matrixes to get better visual analysis. All it is made with the original dataframe. And the result
is a new dataframe with columns reordered, to let you re-use it wherever you want.

Input parameters:

-   _method_ - 
-   _model_ - , default: 
-   _cluster_ - , default: 


## Installation

```sh
pip install recorpy
```

## Usage


```python
        >>> df = pd.DataFrame(np.random.rand(3,3))
        >>> ReorderCorr(df)
```

## Development setup

```sh
$ python3 -m venv env
$ . env/bin/activate
$ make deps
$ tox
```

## Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Make sure to add or update tests as appropriate.

Use [Black](https://black.readthedocs.io/en/stable/) for code formatting and [Conventional Commits](https://www.conventionalcommits.org/en/v1.0.0-beta.4/) for commit messages.

## [Changelog](CHANGELOG.md)

## License

[GPL](https://choosealicense.com/licenses/gpl/)

<!-- Badges -->

[pypi-image]: https://img.shields.io/pypi/v/recorpy
[pypi-url]: https://pypi.org/project/recorpy/
[build-image]: https://github.com/thebooort/recorpy/actions/workflows/python-app.yml/badge.svg
[build-url]: https://github.com/thebooort/recorpy/actions/workflows/python-app.yml
envawareconfig 0.2.1
Load configurations from yaml files with automatic environment variable substitution
Requires Python: >=3.9,<4.0

# Envawareconfig

Load configurations from yaml files with automatic environment variable substitution.

## Installation

with [pip](https://pip.pypa.io/en/stable/):

`pip install envawareconfig`

with [poetry](https://python-poetry.org/):

`poetry add envawareconfig`

## QuickStart

Suppose you have a configuration file like this:

```yaml
# test-config.yaml
database:
  name: my-database
  user: "${DB_USER:admin}"
  password: "${DB_PASSWORD}"
```

and that you have set the environment variable `DB_PASSWORD` to `my-secret-password`
while `DB_USER` has been left unset.

then running the following code:

```python
# main.py

from envawareconfig import load_config

config = load_config("tests/test-config.yaml")
```

would result in:
```python
config = {
    "database": {
        "name": "my-database",
        "user": "admin",
        "password": "my-secret-password"
    }
}
```

Notice that `${DB_PASSWORD}` has been expanded and `${DB_USER:admin}` used the default value.