{"id":23585416,"url":"https://github.com/linogaliana/python-datascientist","last_synced_at":"2025-04-04T17:05:39.112Z","repository":{"id":37089843,"uuid":"280161677","full_name":"linogaliana/python-datascientist","owner":"linogaliana","description":"Dépôt associé au cours Python pour data scientists (ENSAE 2e année)","archived":false,"fork":false,"pushed_at":"2025-03-25T08:16:10.000Z","size":797421,"stargazers_count":124,"open_issues_count":3,"forks_count":46,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-28T16:04:59.447Z","etag":null,"topics":["data-science","jupyter","jupyter-notebook","machine-learning","opendata","python","teaching"],"latest_commit_sha":null,"homepage":"https://pythonds.linogaliana.fr/","language":"Python","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/linogaliana.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-07-16T13:29:53.000Z","updated_at":"2025-03-24T20:16:22.000Z","dependencies_parsed_at":"2023-10-12T21:20:55.876Z","dependency_job_id":"8cc2eee3-a536-46da-8740-1516b5e5a222","html_url":"https://github.com/linogaliana/python-datascientist","commit_stats":{"total_commits":788,"total_committers":14,"mean_commits":"56.285714285714285","dds":0.08121827411167515,"last_synced_commit":"ab0eb6e9918305a87e5199ef88601adda2acd82d"},"previous_names":[],"tags_count":10,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linogaliana%2Fpython-datascientist","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linogaliana%2Fpython-datascientist/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linogaliana%2Fpython-datascientist/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linogaliana%2Fpython-datascientist/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/linogaliana","download_url":"https://codeload.github.com/linogaliana/python-datascientist/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247217174,"owners_count":20903008,"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-science","jupyter","jupyter-notebook","machine-learning","opendata","python","teaching"],"created_at":"2024-12-27T03:14:58.291Z","updated_at":"2025-04-04T17:05:39.084Z","avatar_url":"https://github.com/linogaliana.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Data science with Python \u003cimg height=\"28\" width=\"28\" src=\"https://cdn.simpleicons.org/python/00ccff99\" /\u003e\n[![DOI](https://zenodo.org/badge/280161677.svg)](https://zenodo.org/badge/latestdoi/280161677) [![Production deployment](https://github.com/linogaliana/python-datascientist/actions/workflows/prod.yml/badge.svg)](https://github.com/linogaliana/python-datascientist/actions/workflows/prod.yml)\n\n\u003e [!TIP]\n\u003e **Accessing content using Jupyter Notebooks:**\n\u003e\n\u003e `Pandas` tutorial example (English version)\n\u003e\n\u003e \u003ca href=\"https://datalab.sspcloud.fr/launcher/ide/vscode-python?autoLaunch=true\u0026amp;name=%C2%AB02_pandas_intro%C2%BB\u0026amp;init.personalInit=%C2%ABhttps%3A%2F%2Fraw.githubusercontent.com%2Flinogaliana%2Fpython-datascientist%2Fmain%2Fsspcloud%2Finit-vscode.sh%C2%BB\u0026amp;init.personalInitArgs=%C2%ABen/manipulation%2002_pandas_intro%20correction%C2%BB\" target=\"_blank\" rel=\"noopener\" data-original-href=\"https://datalab.sspcloud.fr/launcher/ide/vscode-python?autoLaunch=true\u0026amp;name=%C2%AB02_pandas_intro%C2%BB\u0026amp;init.personalInit=%C2%ABhttps%3A%2F%2Fraw.githubusercontent.com%2Flinogaliana%2Fpython-datascientist%2Fmain%2Fsspcloud%2Finit-vscode.sh%C2%BB\u0026amp;init.personalInitArgs=%C2%ABen/manipulation%2002_pandas_intro%20correction%C2%BB\"\u003e\u003cimg src=\"https://custom-icon-badges.demolab.com/badge/SSP%20Cloud-Lancer_avec_VSCode-blue?logo=vsc\u0026amp;logoColor=white\" alt=\"Onyxia\"\u003e\u003c/a\u003e\n\u003ca href=\"https://datalab.sspcloud.fr/launcher/ide/jupyter-python?autoLaunch=true\u0026amp;name=%C2%AB02_pandas_intro%C2%BB\u0026amp;init.personalInit=%C2%ABhttps%3A%2F%2Fraw.githubusercontent.com%2Flinogaliana%2Fpython-datascientist%2Fmain%2Fsspcloud%2Finit-jupyter.sh%C2%BB\u0026amp;init.personalInitArgs=%C2%ABen/manipulation%2002_pandas_intro%20correction%C2%BB\" target=\"_blank\" rel=\"noopener\" data-original-href=\"https://datalab.sspcloud.fr/launcher/ide/jupyter-python?autoLaunch=true\u0026amp;name=%C2%AB02_pandas_intro%C2%BB\u0026amp;init.personalInit=%C2%ABhttps%3A%2F%2Fraw.githubusercontent.com%2Flinogaliana%2Fpython-datascientist%2Fmain%2Fsspcloud%2Finit-jupyter.sh%C2%BB\u0026amp;init.personalInitArgs=%C2%ABen/manipulation%2002_pandas_intro%20correction%C2%BB\"\u003e\u003cimg src=\"https://img.shields.io/badge/SSP%20Cloud-Lancer_avec_Jupyter-orange?logo=Jupyter\u0026amp;logoColor=orange\" alt=\"Onyxia\"\u003e\u003c/a\u003e\n\u003ca href=\"https://colab.research.google.com/github/linogaliana/python-datascientist-notebooks-colab//en/blob/main//notebooks/en/manipulation/02_pandas_intro.ipynb\" target=\"_blank\" rel=\"noopener\" data-original-href=\"https://colab.research.google.com/github/linogaliana/python-datascientist-notebooks-colab//en/blob/main//notebooks/en/manipulation/02_pandas_intro.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e\n\n\n\n\n\u003e [!NOTE]  \n\u003e This is the English 🇬🇧🇺🇸 version of the `README`. If you want to see the French 🇫🇷 version, you can click on the link below:\n\u003e \n\u003e [![fr](https://img.shields.io/badge/lang-fr-red.svg)](https://github.com/linogaliana/python-datascientist/blob/main/doc/README-fr.md)\n\n\n\u003cimg src=\"/content/gif_python.gif\" width=\"250\" /\u003e\n\nThis GitHub repository \u003cimg height=\"18\" width=\"18\" src=\"https://cdn.simpleicons.org/github/00ccff99\" /\u003e\nstores the source files used to build the site\n\u003chttps://pythonds.linogaliana.fr/\u003e.\n\nIt contains the entire course *Python for Data Science* \u003cimg height=\"18\" width=\"18\" src=\"https://cdn.simpleicons.org/python/00ccff99\" /\u003e\nthat I teach in the second year (Master 1) at [ENSAE](https://www.ensae.fr/).\n\n\u003e [!NOTE]  \n\u003e A guide to assist potential contributors is available by clicking the button below:\n\u003e \n\u003e [![`CONTRIBUTING.md`](https://img.shields.io/badge/CONTRIBUTING-fr-red.svg)](https://github.com/linogaliana/python-datascientist/blob/main/doc/CONTRIBUTING-fr.md)\n\n\n## Syllabus\n\nThe syllabus is available [on the ENSAE website](https://www.ensae.fr/courses/1425-python-pour-le-data-scientist) and on the [course website](https://pythonds.linogaliana.fr/).\n\nOverall, it offers a very comprehensive content that can satisfy both beginners in data science and those looking for more advanced content:\n\n1. __Data Manipulation__: standard data manipulation (`Pandas`), geographical data (`Geopandas`), data retrieval (web scraping, API)...\n1. __Data Visualization__: classic visualizations (`Matplotlib`, `Seaborn`), cartography, interactive visualizations (`Plotly`, `Folium`)\n1. __Modeling__: machine learning (`Scikit`), econometrics\n1. __Text Data Processing (NLP)__: introduction to tokenization with `NLTK` and `SpaCy`, modeling...\n1. **Introduction to Modern Data Science**: cloud computing, `ElasticSearch`, continuous integration...\n\nThe content of this site is based on open data, whether French data (mainly from the central platform [`data.gouv`](https://www.data.gouv.fr) or the website of [Insee](https://www.insee.fr)) or American data.\n\nA good complement to the website's content is the course we give with Romain Avouac ([@avouacr](https://github.com/avouacr)) in the final year at ENSAE, more focused on the production of data science projects: [https://ensae-reproductibilite.github.io/website/](https://ensae-reproductibilite.github.io/website/)\n\n\n\u003cdetails\u003e\n\u003csummary\u003e\n\u003ch2\u003e\nTesting Python examples\n\u003c/h2\u003e\n\u003c/summary\u003e\n\nYou can use a personal installation of `Python` or shared servers. On the website, a series of buttons are available to easily test the examples on `Jupyter` notebooks in the configuration that suits you best.\n\n\u003cp\u003e\nHere are, for example, these buttons for the \u003ccode\u003eNumpy\u003c/code\u003e tutorial:\n\u003c/p\u003e\n\n\u003cp class=\"badges\"\u003e\n\u003ca href=\"https://github.com/linogaliana/python-datascientist-notebooks/blob/main/notebooks/course/manipulation/01_numpy.ipynb\" class=\"github\"\u003e\u003ci class=\"fab fa-github\"\u003e\u003c/i\u003e\u003c/a\u003e\n\u003ca href=\"https://downgit.github.io/#/home?url=https://github.com/linogaliana/python-datascientist-notebooks/blob/main/notebooks/course/manipulation/01_numpy.ipynb\" target=\"_blank\" rel=\"noopener\"\u003e\u003cimg src=\"https://img.shields.io/badge/Download-Notebook-important?logo=Jupyter\" alt=\"Download\"\u003e\u003c/a\u003e\n\u003ca href=\"https://datalab.sspcloud.fr/launcher/ide/jupyter-python?autoLaunch=true\u0026amp;onyxia.friendlyName=%C2%ABpython-datascience%C2%BB\u0026amp;init.personalInit=%C2%ABhttps%3A%2F%2Fraw.githubusercontent.com%2Flinogaliana%2Fpython-datascientist-notebooks%2Fmaster%2Fsspcloud%2Finit-jupyter.sh%C2%BB\u0026amp;init.personalInitArgs=%C2%ABmanipulation%2001_numpy%C2%BB\u0026amp;security.allowlist.enabled=false\" target=\"_blank\" rel=\"noopener\"\u003e\u003cimg src=\"https://img.shields.io/badge/SSPcloud-Tester%20via%20SSP--cloud-informational\u0026amp;color=yellow?logo=Python\" alt=\"Onyxia\"\u003e\u003c/a\u003e\u003cbr\u003e\n\u003ca href=\"https://colab.research.google.com/github/linogaliana/python-datascientist-notebooks/blob/main/notebooks/course/manipulation/01_numpy.ipynb\" target=\"_blank\" rel=\"noopener\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e\n\u003c/p\u003e\n\n\n\u003c/details\u003e\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flinogaliana%2Fpython-datascientist","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flinogaliana%2Fpython-datascientist","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flinogaliana%2Fpython-datascientist/lists"}