{"id":19302872,"url":"https://github.com/surajwate/datalab","last_synced_at":"2026-01-30T08:06:07.613Z","repository":{"id":254889234,"uuid":"847854196","full_name":"surajwate/DataLab","owner":"surajwate","description":"DataLab is a versatile toolkit designed to simplify data exploration, analysis, and visualization for data scientists.","archived":false,"fork":false,"pushed_at":"2025-03-17T11:26:38.000Z","size":818,"stargazers_count":0,"open_issues_count":6,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-05-02T15:10:59.063Z","etag":null,"topics":["data-analysis","data-science","python","visualization"],"latest_commit_sha":null,"homepage":"http://surajwate.com/DataLab/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/surajwate.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2024-08-26T17:11:21.000Z","updated_at":"2024-12-19T04:13:39.000Z","dependencies_parsed_at":"2024-08-26T20:45:51.768Z","dependency_job_id":"c05a3f24-55da-4675-b0bf-12f36cc240f7","html_url":"https://github.com/surajwate/DataLab","commit_stats":null,"previous_names":["surajwate/datalab"],"tags_count":6,"template":false,"template_full_name":null,"purl":"pkg:github/surajwate/DataLab","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/surajwate%2FDataLab","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/surajwate%2FDataLab/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/surajwate%2FDataLab/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/surajwate%2FDataLab/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/surajwate","download_url":"https://codeload.github.com/surajwate/DataLab/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/surajwate%2FDataLab/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":260244982,"owners_count":22980112,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-analysis","data-science","python","visualization"],"created_at":"2024-11-09T23:24:07.586Z","updated_at":"2026-01-30T08:06:07.608Z","avatar_url":"https://github.com/surajwate.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# suraj_datalab\n\n[![PyPI version](https://img.shields.io/pypi/v/suraj_datalab.svg)](https://pypi.org/project/suraj_datalab/)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n[![Build Status](https://github.com/surajwate/DataLab/actions/workflows/publish.yml/badge.svg)](https://github.com/surajwate/DataLab/actions)\n\n`suraj_datalab` is a Python package designed to streamline the process of analyzing and visualizing both categorical and numerical data. It also includes utilities for data cleaning and preparing datasets for machine learning models, like creating K-Folds for cross-validation.\n\n## Table of Contents\n\n- [Features](#features)\n- [Installation](#installation)\n- [Quickstart](#quickstart)\n- [Usage](#usage)\n- [Examples](#examples)\n- [API Reference](#api-reference)\n- [Contributing](#contributing)\n- [License](#license)\n- [Acknowledgments](#acknowledgments)\n- [Contact](#contact)\n\n## Features\n\n- **Categorical Analysis**: Effortlessly analyze and visualize categorical data in relation to target variables.\n- **Numerical Analysis**: Detect, analyze, and visualize outliers in numerical data.\n- **Data Cleaning**: Automatically handle rare categories in your datasets.\n- **Cross-Validation Preparation**: Create K-Folds for both classification and regression tasks, including stratified K-Folds.\n- **Visualization**: Built-in support for generating insightful plots with minimal code.\n- **Extensible**: Designed with flexibility in mind, allowing easy extension and integration with other data processing workflows.\n\n## Installation\n\n### Requirements\n\n- Python 3.12 or higher\n- [pandas](https://pandas.pydata.org/)\n- [seaborn](https://seaborn.pydata.org/)\n- [matplotlib](https://matplotlib.org/)\n\n### Install via pip\n\n```bash\npip install suraj_datalab\n```\n\n## Quickstart\n\nHere’s how you can quickly get started with `suraj_datalab`:\n\n```python\nimport pandas as pd\nfrom suraj_datalab.analyze import categorical_feature, numerical_feature\n\n# Sample DataFrame\ndata = {'Feature': ['A', 'B', 'A', 'B'], 'Transported': [True, False, True, False]}\ndf = pd.DataFrame(data)\n\n# Analyze categorical feature\nresult = categorical_feature(df, 'Feature', 'Transported')\nprint(result)\n```\n\n## Usage\n\nFor detailed usage instructions, please refer to the [Usage Guide](https://surajwate.com/DataLab/usage/).\n\n## Examples\n\nCheck out the [Examples](https://surajwate.com/DataLab/examples/) section for practical examples of how to use the functions and classes provided by `suraj_datalab`.\n\n## API Reference\n\nFor a detailed reference of all available functions and classes, see the [API Reference](https://surajwate.com/DataLab/api_reference/).\n\n## Contributing\n\nContributions are welcome! Please read the [Contributing Guidelines](CONTRIBUTING.md) for more details.\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## Acknowledgments\n\nThanks to all contributors who have helped with this project.\n\n## Contact\n\nFor any questions or suggestions, please contact [Suraj Wate](mailto:surajwate@gmail.com).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsurajwate%2Fdatalab","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsurajwate%2Fdatalab","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsurajwate%2Fdatalab/lists"}