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Multilingual version as quarto profile (#533)
* Add profiles * First test * project * csv no commit * up * multilingual numpy * switch * finalizing * up * Modularisation * no if * intro * render all * format * replace master by main
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‎.github/workflows/manual-test.yaml‎

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conda list
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- name: Convert in ipynb with Quarto
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run: |
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rm -f _quarto.yml
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cp _quarto-prod.yml _quarto.yml
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export QUARTO_PROFILE=fr,en
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quarto --version
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git diff --name-only origin/master origin/${GITHUB_HEAD_REF} >> diff
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git diff --name-only origin/main origin/${GITHUB_HEAD_REF} >> diff
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python build/tweak_render.py
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python build/pimp_notebook.py
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quarto render content --to ipynb

‎.github/workflows/netlify-test.yaml‎

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run: git config --global --add safe.directory /__w/python-datascientist/python-datascientist
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- name: Render website
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run: |
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rm -f _quarto.yml
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cp _quarto-prod.yml _quarto.yml
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export QUARTO_PROFILE=dev
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quarto --version
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git diff --name-only origin/master origin/${GITHUB_HEAD_REF} | grep -v '/_' >> diff
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python build/append_environment.py
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python build/tweak_render.py
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cat _quarto.yml
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quarto render --to html
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- name: Install npm
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if: ${{ github.event.pull_request.head.repo.full_name == github.repository }}
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conda list
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- name: Convert in ipynb with Quarto
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run: |
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rm -f _quarto.yml
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cp _quarto-prod.yml _quarto.yml
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export QUARTO_PROFILE=dev
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quarto --version
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git diff --name-only origin/master origin/${GITHUB_HEAD_REF} | grep -v '/_' >> diff
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python build/tweak_render.py
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python build/pimp_notebook.py
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quarto render content --to ipynb

‎.github/workflows/prod.yml‎

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run: git config --global --add safe.directory /__w/python-datascientist/python-datascientist
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- name: Render website
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run: |
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rm -f _quarto.yml
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cp _quarto-prod.yml _quarto.yml
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export QUARTO_PROFILE=fr,en
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python build/append_environment.py
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quarto render --to html
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- name: Publish to Pages
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if: github.ref == 'refs/heads/master'
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if: github.ref == 'refs/heads/main'
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run: |
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git config --global user.email quarto-github-actions-publish@example.com
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git config --global user.name "Quarto GHA Workflow Runner"
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conda list
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- name: Convert in ipynb with Quarto
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run: |
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rm -f _quarto.yml
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cp _quarto-prod.yml _quarto.yml
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find content -type f -name "*.qmd" ! -name "_*" >> diff
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cat diff
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python build/tweak_render.py
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python build/pimp_notebook.py
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export QUARTO_PROFILE=fr,en
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quarto render content --to ipynb
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mkdir -p temp_notebooks
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mkdir -p temp_notebooks/notebooks

‎.gitignore‎

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_book/
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_site/
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*index.ipynb
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*.csv
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*.parquet
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*.ipynb
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*.ipynb_checkpoints/
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.jupyter_cache/
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_freeze/
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content/manipulation/cog_2023.csv
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*_black_formatted.py
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*.png
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*.jpg

‎README.md‎

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[![build-doc Actions Status](https://github.com/linogaliana/python-datascientist/actions/workflows/prod.yml/badge.svg)](https://github.com/linogaliana/python-datascientist/actions)
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<a href="https://github.com/linogaliana/python-datascientist/blob/master/notebooks/course/manipulation/01_numpy.ipynb" class="github"><i class="fab fa-github"></i></a>
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<a href="https://downgit.github.io/#/home?url=https://github.com/linogaliana/python-datascientist/blob/master/notebooks/course/manipulation/01_numpy.ipynb" target="_blank" rel="noopener"><img src="https://img.shields.io/badge/Download-Notebook-important?logo=Jupyter" alt="Download"></a>
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<a href="https://nbviewer.jupyter.org/github/linogaliana/python-datascientist/blob/master/notebooks/course/manipulation/01_numpy.ipynb" target="_blank" rel="noopener"><img src="https://img.shields.io/badge/Visualize-nbviewer-blue?logo=Jupyter" alt="nbviewer"></a>
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<a href="https://github.com/linogaliana/python-datascientist/blob/main/notebooks/course/manipulation/01_numpy.ipynb" class="github"><i class="fab fa-github"></i></a>
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<a href="https://downgit.github.io/#/home?url=https://github.com/linogaliana/python-datascientist/blob/main/notebooks/course/manipulation/01_numpy.ipynb" target="_blank" rel="noopener"><img src="https://img.shields.io/badge/Download-Notebook-important?logo=Jupyter" alt="Download"></a>
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<a href="https://nbviewer.jupyter.org/github/linogaliana/python-datascientist/blob/main/notebooks/course/manipulation/01_numpy.ipynb" target="_blank" rel="noopener"><img src="https://img.shields.io/badge/Visualize-nbviewer-blue?logo=Jupyter" alt="nbviewer"></a>
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<a href="https://datalab.sspcloud.fr/launcher/ide/jupyter-python?autoLaunch=true&onyxia.friendlyName=%C2%ABpython-datascience%C2%BB&init.personalInit=%C2%ABhttps%3A%2F%2Fraw.githubusercontent.com%2Flinogaliana%2Fpython-datascientist%2Fmaster%2Fsspcloud%2Finit-jupyter.sh%C2%BB&init.personalInitArgs=%C2%ABmanipulation%2001_numpy%C2%BB&security.allowlist.enabled=false" target="_blank" rel="noopener"><img src="https://img.shields.io/badge/SSPcloud-Tester%20via%20SSP--cloud-informational&amp;color=yellow?logo=Python" alt="Onyxia"></a><br>
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<a href="http://colab.research.google.com/github/linogaliana/python-datascientist/blob/master/notebooks/course/manipulation/01_numpy.ipynb" target="_blank" rel="noopener"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>
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<a href="http://colab.research.google.com/github/linogaliana/python-datascientist/blob/main/notebooks/course/manipulation/01_numpy.ipynb" target="_blank" rel="noopener"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>
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[![DOI](https://zenodo.org/badge/280161677.svg)](https://zenodo.org/badge/latestdoi/280161677)
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et sont maintenant stockés sur un [dépôt à part](https://github.com/linogaliana/python-datascientist-notebooks).
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L'environnement `Conda` nécessaire pour faire tourner l'ensemble du
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cours est disponible dans un fichier [`environment.yml`](https://github.com/linogaliana/python-datascientist-docker/blob/master/environment.yml).
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cours est disponible dans un fichier [`environment.yml`](https://github.com/linogaliana/python-datascientist-docker/blob/main/environment.yml).
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Il est recommandé d'utiliser la `conda-forge` afin de bénéficier de versions
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récentes des packages.
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</details>

‎_quarto-dev.yml‎

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project:
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type: website
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render:
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- index.qmd
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- content/getting-started/index.qmd
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- content/getting-started/01_installation.qmd
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- content/getting-started/02_DS_environment.qmd
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- content/getting-started/03_data_analysis.qmd
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- content/getting-started/04_python_practice.qmd
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- content/getting-started/05_rappels_types.qmd
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- content/getting-started/06_rappels_fonctions.qmd
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- content/getting-started/07_rappels_classes.qmd
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- content/manipulation/index.qmd
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- content/manipulation/01_numpy.qmd
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- content/manipulation/01_numpy_en.qmd
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- content/visualisation/index.qmd
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- content/modelisation/index.qmd
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- content/NLP/index.qmd
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- content/annexes/evaluation.qmd
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website:
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title: "Python pour la data science"
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page-footer:
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left: |
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Python pour la _data science_, Lino Galiana.<br>
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Licence {{< fa brands creative-commons >}}<br>
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Code source disponible sur [`Github`](https://github.com/linogaliana/python-datascientist)
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right: |
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Site construit avec {{< fa brands python >}} et [`Quarto`](https://quarto.org/)<br>
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Inspiration pour la mise en forme du site [ici](https://www.andreashandel.com)<br>
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[Code source disponible sur {{< fa brands github >}} `GitHub`](https://github.com/linogaliana/python-datascientist)
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sidebar:
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- id: home
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title: "Homepage"
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href: index.qmd
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- id: introduction
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title: "Introduction"
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#collapse-level: 2
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contents:
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- content/getting-started/index.qmd
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- content/getting-started/01_installation.qmd
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- content/getting-started/02_DS_environment.qmd
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- content/getting-started/03_data_analysis.qmd
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- content/getting-started/04_python_practice.qmd
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- content/getting-started/05_rappels_types.qmd
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- content/getting-started/06_rappels_fonctions.qmd
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- content/getting-started/07_rappels_classes.qmd
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- id: manipulation
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title: "Manipuler"
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#collapse-level: 2
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contents:
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- href: content/manipulation/index.qmd
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text: "Introduction"
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- content/manipulation/01_numpy.qmd
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- content/manipulation/02_pandas_intro.qmd
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- content/manipulation/02_pandas_suite.qmd
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- content/manipulation/03_geopandas_intro.qmd
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- content/manipulation/04a_webscraping_TP.qmd
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- content/manipulation/04c_API_TP.qmd
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- content/manipulation/04b_regex_TP.qmd
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- id: communication
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title: "Communiquer"
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#collapse-level: 2
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contents:
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- href: content/visualisation/index.qmd
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text: "Introduction"
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- content/visualisation/matplotlib.qmd
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- content/visualisation/maps.qmd
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- id: modelisation
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title: "Modéliser"
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#collapse-level: 2
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contents:
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- href: content/modelisation/index.qmd
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text: "Introduction"
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- content/modelisation/0_preprocessing.qmd
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- content/modelisation/1_modelevaluation.qmd
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- content/modelisation/2_SVM.qmd
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- content/modelisation/3_regression.qmd
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- content/modelisation/4_featureselection.qmd
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- content/modelisation/5_clustering.qmd
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- content/modelisation/6_pipeline.qmd
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- content/modelisation/7_mlapi.qmd
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- id: NLP
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title: "NLP"
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#collapse-level: 2
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contents:
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- href: content/NLP/index.qmd
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text: "Introduction"
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- content/NLP/01_intro.qmd
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- content/NLP/02_exoclean.qmd
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- content/NLP/03_lda.qmd
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- content/NLP/04_word2vec.qmd
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- content/NLP/05_exo_supp.qmd
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- id: modern
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title: "Approfondissements"
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#collapse-level: 2
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contents:
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- href: content/modern-ds/index.qmd
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text: "Introduction"
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- content/modern-ds/continuous_integration.qmd
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- content/modern-ds/dallE.qmd
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- content/modern-ds/s3.qmd
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- content/modern-ds/elastic_approfondissement.qmd
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- content/modern-ds/elastic_intro.qmd
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- id: git
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title: "Git"
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#collapse-level: 2
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contents:
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- href: content/git/index.qmd
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text: "Introduction"
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- content/git/introgit.qmd
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- content/git/exogit.qmd
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- id: appendix
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title: "Annexes"
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#collapse-level: 2
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contents:
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- content/annexes/evaluation.qmd
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- content/annexes/corrections.qmd
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- href: https://linogaliana.github.io/python-datascientist-slides/#/title-slide
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text: "Slides de présentation"
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citation:
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title: "Python pour la data science"
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author: Lino Galiana
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type: book
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doi: "10.5281/zenodo.8229676"
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url: https://pythonds.linogaliana.fr/
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issued: 2023
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‎_quarto-en.yml‎

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project:
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type: website
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output-dir: "./_site/en"
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render:
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- index.qmd
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# English content
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- content/manipulation/01_numpy.qmd
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- content/manipulation/02_pandas_intro.qmd
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lang: en
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website:
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title: "Python for data science"
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page-footer:
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left: |
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Python pour la _data science_, Lino Galiana.<br>
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Licence {{< fa brands creative-commons >}}<br>
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Code source disponible sur [`Github`](https://github.com/linogaliana/python-datascientist)
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right: |
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Site construit avec {{< fa brands python >}} et [`Quarto`](https://quarto.org/)<br>
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Inspiration pour la mise en forme du site [ici](https://www.andreashandel.com)<br>
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[Code source disponible sur {{< fa brands github >}} `GitHub`](https://github.com/linogaliana/python-datascientist)
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body-header: |
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<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.7.0/css/font-awesome.min.css">
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<a href="#" onclick="this.href = location.href.replace('/en/', '/');" class="button-cta">
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<button class="btn"><i class="fa fa-language"></i> Passer à la version française 🇫🇷</button>
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</a>
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sidebar:
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- id: introduction
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title: "Introduction"
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#collapse-level: 2
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contents:
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- content/getting-started/index.qmd
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- content/getting-started/01_installation.qmd
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- content/getting-started/02_DS_environment.qmd
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- content/getting-started/03_data_analysis.qmd
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- content/getting-started/04_python_practice.qmd
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- content/getting-started/05_rappels_types.qmd
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- content/getting-started/06_rappels_fonctions.qmd
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- content/getting-started/07_rappels_classes.qmd
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- id: manipulation
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title: "Wrangle"
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#collapse-level: 2
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contents:
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- href: content/manipulation/index.qmd
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text: "Introduction"
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- content/manipulation/01_numpy.qmd
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- content/manipulation/02_pandas_intro.qmd
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- content/manipulation/02_pandas_suite.qmd
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- content/manipulation/03_geopandas_intro.qmd
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- content/manipulation/04a_webscraping_TP.qmd
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- content/manipulation/04c_API_TP.qmd
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- content/manipulation/04b_regex_TP.qmd
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- id: communication
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title: "Communicate"
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#collapse-level: 2
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contents:
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- href: content/visualisation/index.qmd
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text: "Introduction"
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- content/visualisation/matplotlib.qmd
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- content/visualisation/maps.qmd
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- id: modelisation
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title: "Model"
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#collapse-level: 2
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contents:
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- href: content/modelisation/index.qmd
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text: "Introduction"
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- content/modelisation/0_preprocessing.qmd
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- content/modelisation/1_modelevaluation.qmd
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- content/modelisation/2_SVM.qmd
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- content/modelisation/3_regression.qmd
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- content/modelisation/4_featureselection.qmd
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- content/modelisation/5_clustering.qmd
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- content/modelisation/6_pipeline.qmd
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- content/modelisation/7_mlapi.qmd
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- id: NLP
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title: "NLP"
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#collapse-level: 2
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contents:
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- href: content/NLP/index.qmd
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text: "Introduction"
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- content/NLP/01_intro.qmd
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- content/NLP/02_exoclean.qmd
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- content/NLP/03_lda.qmd
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- content/NLP/04_word2vec.qmd
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- content/NLP/05_exo_supp.qmd
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- id: modern
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title: "In-depth"
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#collapse-level: 2
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contents:
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- href: content/modern-ds/index.qmd
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text: "Introduction"
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- content/modern-ds/continuous_integration.qmd
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- content/modern-ds/s3.qmd
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- content/modern-ds/elastic_approfondissement.qmd
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- content/modern-ds/elastic_intro.qmd
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- id: git
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title: "Git"
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#collapse-level: 2
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contents:
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- href: content/git/index.qmd
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text: "Introduction"
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- content/git/introgit.qmd
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- content/git/exogit.qmd
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- id: appendix
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title: "Annexes"
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#collapse-level: 2
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contents:
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- content/annexes/evaluation.qmd
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- content/annexes/corrections.qmd
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- href: https://linogaliana.github.io/python-datascientist-slides/#/title-slide
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text: "Slides de présentation"
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citation:
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title: "Python pour la data science"
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author: Lino Galiana
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type: book
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doi: "10.5281/zenodo.8229676"
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url: https://pythonds.linogaliana.fr/
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issued: 2023
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