semvec/pypi-packages huggingface dataset:
clustering-imputation 1.0.1
Adding correlation to handle MNAR
Keywords: python, imputation, MNAR


# Clustering Imputation
## Installation
To install the package, run:
```bash
pip install clustering-imputation==1.0.0
```
## Usage

```python
from clustering_imputation import clusterImputer
df = ...  # Load your dataset
x = clusterImputer(df, "mice", "mean", 0.4, 10)
x.impute()
```
# About the Package

## Problem Statement

* Traditional imputation techniques face several challenges:

* High-Dimensional and Sparse Data: Existing methods struggle with large, sparse datasets; efficient techniques for such cases are needed.

* Temporal Dependencies: Current methods often overlook temporal correlations in data.
## Need to develop a new algo
* Non-Random Missingness: Few methods address non-random missing patterns; improvements here could boost real-world application accuracy. We aim to develop an imputation method that considers "Missing Not at Random" (MNAR).

* Computational Complexity: MICE and EM methods are computationally expensive for high-dimensional data. Our approach aims to reduce time complexity.

## Philosophy of Our Solution: Clustered MICE/EM

We propose a clustering-based approach:

* Identify correlations between features.

* Apply MICE/EM within clusters rather than on the entire dataset.

* Combine results to reconstruct the dataset.

* This method effectively handles MNAR data by leveraging feature correlations.
For further details refer this [ppt](https://docs.google.com/presentation/d/1UZ2uDkleSgB2ZttjG1D6nmQhqk7uz5FQRW5UmSkB0Sg/edit?usp=sharing)
## Contributing

Pull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.

Please make sure to update tests as appropriate.
marimo-extra 1.0.3
Add your description here
Requires Python: >=3.12

# Marimo Extra

# Usage

1. Create `index.py` with `marimo` notebook
2. Create `scripts/website_build.py` which will be run to generate `HTML` files
3. Push to `master` branch
4. Go to repository **Settings > Pages** and change the "Source" dropdown to "GitHub Actions"
5. GitHub Actions will automatically build and deploy to Pages

# Feature

* [X] Marimo Exporter
  * [X] Generate Export CMD
  * [X] Export function (Defult: Static HTML)
  * [X] Spesial Function
    * [X] Export Executable Notebook (Run HTML-WASM)
    * [X] Export Editable Notebook (Edit HTML-WASM)
    * [X] Export App Notebook (with out code Run HTML-WASM)
* [X] Autometed Website Build
  * [ ] Generate Index Notebook
    * [X] Collect available Notebooks
      * [X] Convert Notebook with Exporter (Besed on Dir Structure)
      * [X] Link them with Marimo Navigator
pytest-pylyzer 0.1.0
A pytest plugin for pylyzer
Requires Python: >=3.10
Keywords: pylyzer, pytest

# pytest-pylyzer

[![check](https://github.com/LoicRiegel/pytest-pylyzer/actions/workflows/check.yaml/badge.svg)](https://github.com/LoicRiegel/pytest-pylyzer/actions/workflows/check.yaml)

A [pytest](https://docs.pytest.org/en/stable/) plugin to run [pylyzer](https://github.com/mtshiba/pylyzer), a static code analyzer / language server for Python, written in Rust.

## Installation

```
pip install pytest-pylyzer
```
Or include `pytest-pylyzer` in your project's dev-dependencies.

## Usage

```
pytest --pylyzer
```
The plugin will run one `pylyzer` check test per file and fail if `pylyzer` detects any errors in that file.

## Contributing

Contributions are very welcome.

Use ``tox`` to make sure that the tests pass against all supported python versions and that the code is linted and formatted.

## License

Distributed under the terms of the [MIT](./LICENSE) license. This is free and open source software.