{"id":22766974,"url":"https://github.com/ejdecena/herramientas-python","last_synced_at":"2025-04-13T04:50:38.000Z","repository":{"id":37610008,"uuid":"208773865","full_name":"ejdecena/Herramientas-Python","owner":"ejdecena","description":"Herramientas fundamentales de Python para Cálculo Numérico y Ciencia de Datos.","archived":false,"fork":false,"pushed_at":"2023-07-06T21:42:47.000Z","size":9646,"stargazers_count":3,"open_issues_count":2,"forks_count":1,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-03-26T21:46:59.298Z","etag":null,"topics":["calculo-numerico","ciencia-de-datos","data-science","datascience","herramientas-python","ipynb","jupyter","jupyter-notebook","lenguaje-python","matplotlib","matplotlib-tutorial","metodos-numericos","numpy-tutorial","pandas-tutorial","python3","scikit-learn","scikitlearn-machine-learning","scipy","statsmodels"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/ejdecena.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","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}},"created_at":"2019-09-16T10:35:45.000Z","updated_at":"2023-09-11T05:48:29.000Z","dependencies_parsed_at":"2025-02-05T12:35:29.104Z","dependency_job_id":"aebbcce3-a7da-4dae-b9bc-ab1292356945","html_url":"https://github.com/ejdecena/Herramientas-Python","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ejdecena%2FHerramientas-Python","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ejdecena%2FHerramientas-Python/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ejdecena%2FHerramientas-Python/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ejdecena%2FHerramientas-Python/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ejdecena","download_url":"https://codeload.github.com/ejdecena/Herramientas-Python/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248665755,"owners_count":21142123,"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":["calculo-numerico","ciencia-de-datos","data-science","datascience","herramientas-python","ipynb","jupyter","jupyter-notebook","lenguaje-python","matplotlib","matplotlib-tutorial","metodos-numericos","numpy-tutorial","pandas-tutorial","python3","scikit-learn","scikitlearn-machine-learning","scipy","statsmodels"],"created_at":"2024-12-11T13:16:08.727Z","updated_at":"2025-04-13T04:50:37.972Z","avatar_url":"https://github.com/ejdecena.png","language":"Jupyter Notebook","readme":"\u003cdiv align = \"center\"\u003e\n    \u003cimg src = \"imagenes/python_logo.jpeg\" width = \"70\" height = \"70\" /\u003e\n\u003c/div\u003e\n\n# Herramientas Python.\n\n*Herramientas Python* es un conjunto de notebooks de aprendizaje sobre las librerías fundamentales para los cursos de *Cálculo Numérico* y *Ciencia de Datos* en [*Python*](https://www.python.org).\n\n\u003ca href=\"https://nbviewer.jupyter.org/github/ejdecena/herramientas_python/tree/master/\"\u003e\u003cimg src=\"https://img.shields.io/badge/Visualizar-NBViewer-orange\"/\u003e\u003c/a\u003e \u003cimg src=\"https://img.shields.io/badge/License-MIT-green\" /\u003e \u003cimg src=\"https://img.shields.io/badge/Python-3.5-blue\" /\u003e\n\n## Desarrollador.\n\n* [Ing. Edgard Decena.](mailto:edecena@gmail.com)\n\n## Indice de contenido.\n\n* [**Numpy**](01_numpy.ipynb): Librería para el manejo y cálculo numérico de matrices y vectores.\n* [**Matplotlib**](02_matplotlib.ipynb): Librería para la visualización de datos en 2D y 3D.\n* [**Scipy**](03_scipy.ipynb): Librería que contiene distintos algoritmos de cálculo numérico y optimización.\n* [**Pandas**](04_pandas.ipynb): Librería para el procesamiento de datos.\n* [**Statsmodels**](05_statsmodels.ipynb): Librería para el análisis y cálculo numérico de funciones estadísticas.\n* [**Scikit Learn**](06_scikit_learn.ipynb): Librería para el desarrollo de modelos de *Aprendizaje Automático*.\n\n## Dependencias.\n\nEste proyecto requiere la instalación de las siguientes dependencias externas:\n\n* *Jupyter 1.0.0* (`$ pip install jupyter`)\n* *Numpy 1.16.4* (`$ pip install numpy`)\n* *Matplotlib 3.0.3* (`$ pip install matplotlib`)\n* *Seaborn 0.9.0* (`$ pip install seaborn`)\n* *Scipy 1.3.0* (`$ pip install scipy`)\n* *Xlrd 1.2.0* (`$ pip install xlrd`)\n* *Pandas 0.24.2* (`$ pip install pandas`)\n* *Statsmodels 0.10.0* (`$ pip install statsmodels`)\n* *Scikit Learn 0.21.2* (`$ pip install scikit-learn`)\n\nEstas dependencias pueden instalarse por separado siguiendo las instrucciones propias en cada notebook, o pueden instalarse todas mediante la ejecución de una única instrucción en la terminal:\n```bash\npip install -r requirements.txt\n```\n\n## TO DO (por hacer).\n\nEste repositorio es un **trabajo en progreso**, por lo que aún están pendientes por hacer las siguientes tareas:\n\n* Completar los notebooks:\n    - [Scipy](03_scipy.ipynb).\n    - [Statsmodels](05_statsmodels.ipynb).\n    - [Scikit Learn](06_scikit_learn.ipynb).\n* Incorporar guías en PDF que complementen los notebooks.\n\n## Contribuciones.\n\nEste repositorio es de *código abierto*; lo que significa que cualquier persona interesada puede contribuir en él. Todas las contribuciones serán bienvenidas, incluyendo:\n\n* Correcciones ortográficas.\n* Nuevas figuras.\n* Correcciones en el código *Python*, incluídas mejoras de estilo.\n* Mejores ejemplos.\n* Mejores explicaciones. \n* Correcciones de errores conceptuales.\n\nLa forma de contribuir es vía la interfaz web de *GitHub*, mediante peticiones de [*Pull requests*](https://github.com/ejdecena/herramientas_python/pulls), o reportando los problemas/bugs del repositorio por [*Issues*](https://github.com/ejdecena/herramientas_python/issues).","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fejdecena%2Fherramientas-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fejdecena%2Fherramientas-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fejdecena%2Fherramientas-python/lists"}