{"id":18614075,"url":"https://github.com/enthought/numpy-tutorial-scipyconf-2023","last_synced_at":"2025-07-31T09:39:15.245Z","repository":{"id":173706784,"uuid":"650692913","full_name":"enthought/Numpy-Tutorial-SciPyConf-2023","owner":"enthought","description":"Public GitHub repo for SciPy 2023 tutorial (Introduction to Numerical Computing With NumPy)","archived":false,"fork":false,"pushed_at":"2023-07-11T21:06:30.000Z","size":2022,"stargazers_count":8,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-03-25T06:51:10.827Z","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/arr_from_text.npy","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}},"created_at":"2023-06-07T15:48:46.000Z","updated_at":"2024-06-17T17:09:23.000Z","dependencies_parsed_at":null,"dependency_job_id":"cefd16c6-7c8a-40d6-ae57-a8c807abeb27","html_url":"https://github.com/enthought/Numpy-Tutorial-SciPyConf-2023","commit_stats":null,"previous_names":["enthought/numpy-tutorial-scipyconf-2023"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/enthought%2FNumpy-Tutorial-SciPyConf-2023","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/enthought%2FNumpy-Tutorial-SciPyConf-2023/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/enthought%2FNumpy-Tutorial-SciPyConf-2023/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/enthought%2FNumpy-Tutorial-SciPyConf-2023/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/enthought","download_url":"https://codeload.github.com/enthought/Numpy-Tutorial-SciPyConf-2023/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248322123,"owners_count":21084333,"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":[],"created_at":"2024-11-07T03:25:01.266Z","updated_at":"2025-04-11T00:30:28.067Z","avatar_url":"https://github.com/enthought.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# SciPy 2023 Tutorial: Introduction to Numerical Computing With NumPy\n\n#### Presented by: Sandhya Govindaraju, [Enthought, Inc.](https://www.enthought.com)\n\nThis repository contains all the material needed by students registered for the Numpy tutorial of [SciPy 2023](https://www.scipy2023.scipy.org/) on Monday, July 10th 2023.\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-2023/main)\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### Install Packages\n\nTo be able to run the examples, demos and exercises, you must have the following packages installed:\n\n- `ipython` (for running, experimenting, and doing exercises)\n- `jupyterlab` (for access to the Jupyter Notebook web-based interactive computing platform)\n- `matplotlib`\n- `numpy`\n- `pillow`\n- `pyqt`\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\n1. Create a new Anaconda virtual environment by executing the below command in the application window you opened in step 1 above. You may be prompted to `Proceed([y]/n)?`. If so, type `y` and press `Enter`.\n\n    ```\n    conda create -n numpy-tutorial ipython jupyterlab matplotlib numpy pillow pyqt\n    ```\n\n1. Navigate to the directory where you'd like to store materials for this tutorial and download the materials from this GitHub repository by executing the below command. It will create a new folder named `Numpy-Tutorial-SciPyConf-2023/` with all the content you will need.\n\n    ```\n    git clone git@github.com:enthought/Numpy-Tutorial-SciPyConf-2023.git\n    ```\n\n    **NOTE**: If you are not familiar with Git, you can download a zipped archive of the material by clicking on this link: \u003chttps://github.com/enthought/Numpy-Tutorial-SciPyConf-2023/archive/main.zip\u003e. Then, unpack the zipped archive into a directoy named `Numpy-Tutorial-SciPyConf-2023`. You may have to rename the unpacked directory to explicitly be `Numpy-Tutorial-SciPyConf-2023`.\n\n1. To test your installation, please execute the `check_env.py` script in the python virtual environment where you have installed the requirements (from step 2 above).\n\n    If you created an Anaconda environment using the instructions above, you can use the same application window that you opened in step 1, or launch the platform specific application again -- Anaconda Prompt for Windows or Terminal.app for macOS.\n    Be sure to navigate to where you downloaded this GitHub repository and activate your conda environment _before_ executing `python check_env.py`:\n\n    ```\n    # Example path to course materials (yours may differ)\n    $ cd ~/Desktop/Numpy-Tutorial-SciPyConf-2023/\n\n    $ conda activate numpy-tutorial\n\n    $ python check_env.py\n    ```\n\n    You should see a window pop up with a plot that looks vaguely like a smiley face (as shown below).\n\n    ![](assets/images/check_env_output.png)\n\n## Tutorial Materials\n\nThis GitHub repository is all that is needed in terms of tutorial content. If you downloaded these materials in step 3 above, there is no need to do so again. If not, the simplest solution is to download the material using this link:\n\n\u003chttps://github.com/enthought/Numpy-Tutorial-SciPyConf-2023/archive/main.zip\u003e\n\nIf you are familiar with Git, you can also clone this repository with:\n\n```\ngit clone https://github.com/enthought/Numpy-Tutorial-SciPyConf-2023.git\n```\n\nThe above command will create a new folder named `Numpy-Tutorial-SciPyConf-2023/` with all the content you will need: the slides I will go through (`introduction_to_numerical_computing_with_numpy_manual.pdf`), and a folder of exercises.\n\n## Updates\n\nPlease let me know how the tutorial went in [survey]( https://airtable.com/shrzG14g2XdWtt0hC?prefill_Class%20Code=SciPy-2023-Tutorial\u0026hide_Class%20Code=true).\n\nAll the code that was demoed in the class is saved to `history/`\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://scipy2023.slack.com](https://scipy2023.slack.com) .\n\n## Additional Anaconda Resources\n\n- [Managing environments](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html)\n\n  - To create an Anaconda environment from an existing `environment.yml` file:\n\n    ```\n    conda env create -f environment.yml -n numpy-tutorial\n    ```\n\n  - To remove an existing Anaconda environment:\n\n    ```\n    conda remove --name numpy-tutorial --all\n    ```\n\n- To completely uninstall Anaconda, see the \"Uninstalling Anaconda\" documentation [here](https://docs.anaconda.com/anaconda/install/uninstall/).\n\n© 2001-2023, Enthought, Inc.\nAll Rights Reserved. Use only permitted under license. Copying, sharing, redistributing or other unauthorized use strictly prohibited.\nAll trademarks and registered trademarks are the property of their respective owners.\nEnthought, Inc.\n200 W Cesar Chavez Suite 202\nAustin, TX 78701\n\u003cwww.enthought.com\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fenthought%2Fnumpy-tutorial-scipyconf-2023","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fenthought%2Fnumpy-tutorial-scipyconf-2023","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fenthought%2Fnumpy-tutorial-scipyconf-2023/lists"}