semvec/pypi-packages huggingface dataset:
DadosAbertosBrasil 2.0.1
Pacote Python para acesso a dados abertos e APIs do governo brasileiro.
License: MIT
Keywords: brasil, ibge, ipea, ipeadata, camara, deputados, senado, senadores, bacen, bcb, bancocentral, dadosabertos, dadosgovbr

<div align="center">
  <img src="https://raw.githubusercontent.com/GusFurtado/dab_assets/main/images/logo.png"><br>
</div>

---

**Dados Abertos Brasil** é uma iniciativa para facilitar o acesso a dados abertos e APIs do governo brasileiro.

É um pacote open-source para **Python** e **Pandas** e a forma mais simples de acessar dados de instituições como **IGBE**, **IPEA**, **Banco Central**, etc.

Atualmente o pacote Dados Abertos Brasil possui seis módulos, além da classe **[UF](https://www.gustavofurtado.com/dab/DadosAbertosBrasil.uf.html)** que consolida dados diversos de Unidades Federativas em um único objeto.

- DadosAbertosBrasil.**[ibge](https://www.gustavofurtado.com/dab/DadosAbertosBrasil.ibge.html)**
- DadosAbertosBrasil.**[ipea](https://www.gustavofurtado.com/dab/DadosAbertosBrasil.ipea.html)**
- DadosAbertosBrasil.**[camara](https://www.gustavofurtado.com/dab/DadosAbertosBrasil.camara.html)**
- DadosAbertosBrasil.**[senado](https://www.gustavofurtado.com/dab/DadosAbertosBrasil.senado.html)**
- DadosAbertosBrasil.**[bacen](https://www.gustavofurtado.com/dab/DadosAbertosBrasil.bacen.html)**
- DadosAbertosBrasil.**[favoritos](https://www.gustavofurtado.com/dab/DadosAbertosBrasil.favoritos.html)**

### Sobre
- [Documentação](https://www.gustavofurtado.com/dab/index.html)
- [Exemplos](https://github.com/GusFurtado/dab_assets/tree/main/exemplos)

### Instalação
```
pip install DadosAbertosBrasil
```

### Dependências
- [Python 3.10 ou superior](https://www.python.org/)
- [Pandas](https://pandas.pydata.org/)
- [Pydantic](https://docs.pydantic.dev/latest/)
- [Requests](https://requests.readthedocs.io/en/master/)

### Licença
- [MIT](LICENSE)

---

Desenvolvido por: **[Gustavo Furtado](https://www.gustavofurtado.com/)**
dirichlet 1.0.0
Calculates Dirichlet test and plots 2-simplex Dirichlets
License: MIT
Requires Python: >=3.10

Dirichlet
=========

A Python package to estimate the Dirichlet distribution, calculate maximum
likelihood, and test for independence from a variable based on fitting nested
Dirichlet distribution hypotheses.

Most of this package is a port of Thomas P. Minka's wonderful
[Fastfit][fastfit] MATLAB code. Much thanks to him for that and his clear
paper ["Estimating a Dirichlet distribution"][estimating].

[estimating]: http://research.microsoft.com/en-us/um/people/minka/papers/dirichlet/
[fastfit]: http://research.microsoft.com/en-us/um/people/minka/software/fastfit/

Dirichlet Test
--------------

This likelihood ratio test for independence will determine whether two
Dirichlet-distributed data sets are likely to be from the same distribution
or from two different ones, much like a chi-square or G-test for independence,
but with Dirichlet models.

Simplex Plots
-------------

The `dirichlet.simplex` module creates scatter, contour, and filled contour 2-simplex plots. To use this, be sure to install the `simplex` package "extra" (e.g. `pip install dirichlet[simplex]`).

Caveats
-------

Note that this package at the moment doesn't support sparse data vectors due to the
numerical fitting algorithm that uses the gamma function. Possibly some sort of
[additive smoothing](https://en.wikipedia.org/wiki/Additive_smoothing) would
make this package work in your context, but that will depend on your application.

Installation
------------

    pip install dirichlet
    # or
    uv add dirichlet

This has only been tested with Python 3.10+. Other versions may work, but they
haven't been tested.

Development
-----------

To install dev tooling, run:

    uv sync --frozen --locked --all-groups --all-extras

    # To format
    uv run ruff format

    # To test
    uv run pytest

    # To lint
    uv run ruff

A Github workflow will run tests against several Python versions.