{"id":18613999,"url":"https://github.com/enthought/numpy-tutorial-scipyconf-2021","last_synced_at":"2025-08-23T13:39:21.473Z","repository":{"id":48460308,"uuid":"375750151","full_name":"enthought/Numpy-Tutorial-SciPyConf-2021","owner":"enthought","description":"Public GitHub repo for SciPy 2021 tutorial (Introduction to Numerical Computing With NumPy)","archived":false,"fork":false,"pushed_at":"2022-03-22T22:44:18.000Z","size":10604,"stargazers_count":17,"open_issues_count":0,"forks_count":6,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-05-30T16:26:19.613Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/enthought.png","metadata":{"files":{"readme":"README.md","changelog":"history/session1.txt","contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2021-06-10T15:43:26.000Z","updated_at":"2024-08-13T07:53:02.000Z","dependencies_parsed_at":"2022-07-29T01:08:09.193Z","dependency_job_id":null,"html_url":"https://github.com/enthought/Numpy-Tutorial-SciPyConf-2021","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/enthought/Numpy-Tutorial-SciPyConf-2021","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/enthought%2FNumpy-Tutorial-SciPyConf-2021","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/enthought%2FNumpy-Tutorial-SciPyConf-2021/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/enthought%2FNumpy-Tutorial-SciPyConf-2021/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/enthought%2FNumpy-Tutorial-SciPyConf-2021/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/enthought","download_url":"https://codeload.github.com/enthought/Numpy-Tutorial-SciPyConf-2021/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/enthought%2FNumpy-Tutorial-SciPyConf-2021/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":271749193,"owners_count":24814142,"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","status":"online","status_checked_at":"2025-08-23T02:00:09.327Z","response_time":69,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":[],"created_at":"2024-11-07T03:24:38.996Z","updated_at":"2025-08-23T13:39:21.448Z","avatar_url":"https://github.com/enthought.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# SciPy 2021 Tutorial: Introduction to Numerical Computing With NumPy\n\n#### Presented by: Logan Thomas, [Enthought, Inc.](https://www.enthought.com)\n#### YouTube recording of live tutorial [here](https://youtu.be/8L1MgStSZhk)\n\nThis repository contains all the material needed by students registered for the Numpy tutorial of SciPy 2021 on Monday, July 12th 2021.\n\nFor a smooth experience, you will need to make sure that you install or update your Python distribution and download the tutorial material _before_ the day of the tutorial.\n\n## Running the Exercises the (recommended) Easy Way\n\nRun with Binder by clicking this icon: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/enthought/Numpy-Tutorial-SciPyConf-2021/main)\n\n\n## Running the Exercise Locally\n\n### Install Python\n\nIf you don't already have a working python distribution, you may download Anaconda Python ([https://www.anaconda.com/products/individual](https://www.anaconda.com/products/individual)).\n\n\n### Install Packages\n\nTo be able to run the examples, demos and exercises, you must have the following packages installed:\n\n- ipython 7.16+ (for running, experimenting and doing exercises)\n- jupyter 1.0+\n- matplotlib 3.3+\n- numpy 1.17+\n- pillow 7.2+\n- pyqt 5.9+\n\nIf you are using Anaconda, you can use the Anaconda Prompt (Windows) or Terminal.app (macOS) to create an environment with the necessary packages:\n\n1. Open the Anaconda Prompt or Terminal.app using the below instructions:\n    - **Windows**: Click Start and search for \"Anaconda Prompt\". Click on the application to launch a new Anaconda Prompt window.\n    - **macOS**: Open Spotlight Search (using Cmd+Space) and type \"Terminal.app\". Click on the application to launch a new Terminal.app window.   \n\n2. Create a new Anaconda virtual environment by executing the below command in the application window you opened in step 1 above.\n\n    ```\n    $ conda create -n numpy-tutorial ipython jupyter matplotlib numpy pillow pyqt \n    ```\n\n3. To test your installation, please execute the `check_env.py` script in the environment where you have installed the requirements. If you created an Anaconda environment using the instructions above, keep the application window that you opened in step 1 active (or launch the platform specific application again -- Anaconda Prompt for Windows or Terminal.app for macOS), navigate to where you have this GitHub repository, and type:\n\n    ```\n    $ conda activate numpy-tutorial\n    $ python check_env.py\n    ```\n\nYou should see a window pop up with a plot that looks vaguely like a smiley face.\n\n## Download Tutorial Materials\n\nThis GitHub repository is all that is needed in terms of tutorial content. The simplest solution is to download the material using this link:\n\nhttps://github.com/enthought/Numpy-Tutorial-SciPyConf-2021/archive/main.zip\n\nIf you are familiar with Git, you can also clone this repository with:\n\n```\n$ git clone https://github.com/enthought/Numpy-Tutorial-SciPyConf-2021.git\n```\n\nIt will create a new folder named `Numpy-Tutorial-SciPyConf-2021/` with all the content you will need: the slides I will go through (`slides.pdf`), and a folder of exercises.\n\n\n## Questions? Problems?\n\nYou may post messages to the `#tutorial-intro-to-numerical-computing-with-numpy` Slack channel for this tutorial at in the official Slack team: [https://scipy2021.slack.com](https://scipy2021.slack.com) .\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fenthought%2Fnumpy-tutorial-scipyconf-2021","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fenthought%2Fnumpy-tutorial-scipyconf-2021","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fenthought%2Fnumpy-tutorial-scipyconf-2021/lists"}