{"id":23372630,"url":"https://github.com/mardavsj/numpy-in-python","last_synced_at":"2026-04-14T00:03:04.948Z","repository":{"id":219906011,"uuid":"750206443","full_name":"mardavsj/NumPy-in-Python","owner":"mardavsj","description":"The fundamentals of Python NumPy Library.","archived":false,"fork":false,"pushed_at":"2024-02-20T13:09:07.000Z","size":91,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-14T01:48:11.594Z","etag":null,"topics":["analysis-tool","data-manipulation","numpy","numpy-arrays","numpy-matrix","python"],"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/mardavsj.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}},"created_at":"2024-01-30T07:32:50.000Z","updated_at":"2024-02-24T12:40:16.000Z","dependencies_parsed_at":"2024-02-20T14:29:43.215Z","dependency_job_id":"d0f9cb18-80d0-4976-93b2-34987c09a950","html_url":"https://github.com/mardavsj/NumPy-in-Python","commit_stats":null,"previous_names":["mardavsj/numpy-in-python"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mardavsj%2FNumPy-in-Python","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mardavsj%2FNumPy-in-Python/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mardavsj%2FNumPy-in-Python/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mardavsj%2FNumPy-in-Python/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mardavsj","download_url":"https://codeload.github.com/mardavsj/NumPy-in-Python/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247761031,"owners_count":20991533,"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":["analysis-tool","data-manipulation","numpy","numpy-arrays","numpy-matrix","python"],"created_at":"2024-12-21T16:40:01.670Z","updated_at":"2026-04-14T00:03:04.898Z","avatar_url":"https://github.com/mardavsj.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"right\"\u003e\n\n  \u003ca href=\"\"\u003e[![General badge](https://img.shields.io/badge/documentation-red.svg)](https://numpy.org/doc/stable/)\u003c/a\u003e\n  \u003ca href=\"\"\u003e[![license](https://img.shields.io/github/license/mardavsj/NumPy-in-Python.svg)](https://github.com/mardavsj/NumPy-in-Python/blob/main/LICENSE)\u003c/a\u003e\n\n\u003c/div\u003e\n\n![numpy_logo](https://www.davecwright.org/files/sps-files/figures/dave/numpy-logo.png)\n\n\nNumPy stands for Numerical Python. It is a Python library used for working with arrays. It also has functions for working in domain of linear algebra and matrices.\n\nNumPy was created by Travis Oliphant in 2005. It is an open source project and you can use it for free. \n\n[![Python](https://img.shields.io/badge/Python-14354C?style=for-the-badge\u0026logo=python\u0026logoColor=white\u0026color=blue)](https://github.com/python/)\n[![NumPy](https://img.shields.io/badge/numpy-%23013243.svg?style=for-the-badge\u0026logo=numpy\u0026logoColor=white\u0026color=parrotgreen)](https://github.com/numpy/numpy)\n\n\n## Pre-requisites :\n* Python\n* Pip or Conda (depending on user)\n## Installation :\n\nInstall NumPy with pip :\n\n```bash\n  pip install numpy\n```\n\nInstall NumPy with conda :\n\n```bash\n  # Best practice, use an environment rather than install in the base env\n  conda create -n my-env\n  conda activate my-env\n  # If you want to install from conda-forge\n  conda config --env --add channels conda-forge\n  # The actual install command\n  conda install numpy\n```\n\n\n    \n## NumPy Array \n\nNumPy array is a powerful N-dimensional array object and its use in linear algebra, fourier transform and random number capabilities. It provides an array object much faster than traditional Python lists.\n\n#### Types of Array:\n* One Dimensional Array\n* Multi-Dimensional Array\n## Why NumPy Array over Python List ?\n\n* Using an array is faster than a list.\n* A list cannot directly handle a mathematical operations, while array can.\n* An array consumes less memory than a list.\n\n\n\n## Video (NumPy Playlist) \u0026 Blog Tutorial : \n\n[![Video_tutorial](https://img.shields.io/badge/YouTube-FF0000?style=for-the-badge\u0026logo=youtube\u0026logoColor=white)](https://www.youtube.com/playlist?list=PLjVLYmrlmjGfgBKkIFBkMNGG7qyRfo00W)\n[![Blog_tutorial](https://img.shields.io/badge/Medium-12100E?style=for-the-badge\u0026logo=medium\u0026logoColor=black\u0026color=white)](https://medium.com/edureka/python-introduction-to-numpy-numpy-tutorial-4ac06c717971)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmardavsj%2Fnumpy-in-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmardavsj%2Fnumpy-in-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmardavsj%2Fnumpy-in-python/lists"}