Menus automatisés (#432)

* Menus

* test hybrid nagivation

* update

* Update

_quarto.yml

@@ -59,25 +59,17 @@ website:
   reader-mode: true
   navbar:
     background: "white"
+    search: true
     left:
-      - href: index.qmd
+      - file: index.qmd
         text: Home
-      - href: content/getting-started/index.qmd
-        text: Introduction      
-      - href: content/manipulation/index.qmd
-        text: Manipuler des données      
-      - href: content/visualisation/index.qmd
-        text: Visualiser des données      
-      - href: content/modelisation/index.qmd
-        text: Modéliser      
-      - href: content/NLP/index.qmd
-        text: NLP         
-      - href: content/modern-ds/index.qmd
-        text: Approfondissements
-      - href: content/git/index.qmd
-        text: Git {{< fa brands git-alt >}}
-      - href: content/annexes/evaluation.qmd
-        text: Evaluation
+      - sidebar:introduction
+      - sidebar:manipulation
+      - sidebar:communication
+      - sidebar:modelisation
+      - sidebar:modern
+      - sidebar:git
+      - sidebar:appendix
     tools:
       - icon: github
         menu:
@@ -104,81 +96,95 @@ website:
 
 
   sidebar: 
-    style: "docked"
-    search: true
-    contents:
-      - text: "Homepage"
-        href: index.qmd
-      - section: "Introduction"
-        contents:
-          - content/getting-started/index.qmd
-          - content/getting-started/01_installation.qmd
-          - content/getting-started/02_DS_environment.qmd
-          - content/getting-started/03_data_analysis.qmd
-          - content/getting-started/04_python_practice.qmd
-          - content/getting-started/05_rappels_types.qmd
-          - content/getting-started/06_rappels_fonctions.qmd
-          - content/getting-started/07_rappels_classes.qmd
-      - section: "Partie 1: Manipuler des données"
-        contents:
-          - href: content/manipulation/index.qmd
-            text: "Introduction"
-          - content/manipulation/01_numpy.qmd
-          - content/manipulation/02a_pandas_tutorial.qmd
-          - content/manipulation/02b_pandas_TP.qmd
-          - content/manipulation/03_geopandas_tutorial.qmd
-          - content/manipulation/03_geopandas_TP.qmd
-          - content/manipulation/04a_webscraping_TP.qmd
-          - content/manipulation/04c_API_TP.qmd
-          - content/manipulation/04b_regex_TP.qmd
-          - content/manipulation/07_dask.qmd
-      - section: "Partie 2: Communiquer"
-        contents:
-          - href: content/visualisation/index.qmd
-            text: "Introduction"
-          - content/visualisation/matplotlib.qmd
-          - content/visualisation/maps.qmd
-      - section: "Partie 3: Modéliser"
-        contents:
-          - href: content/modelisation/index.qmd
-            text: "Introduction"
-          - content/modelisation/0_preprocessing.qmd
-          - content/modelisation/1_modelevaluation.qmd
-          - content/modelisation/2_SVM.qmd
-          - content/modelisation/3_regression.qmd
-          - content/modelisation/4_featureselection.qmd
-          - content/modelisation/5_clustering.qmd
-          - content/modelisation/6_pipeline.qmd
-      - section: "Partie 4: Natural Langage Processing (NLP)"
-        contents:
-          - href: content/NLP/index.qmd
-            text: "Introduction"
-          - content/NLP/01_intro.qmd
-          - content/NLP/02_exoclean.qmd
-          - content/NLP/03_lda.qmd
-          - content/NLP/04_word2vec.qmd
-          - content/NLP/05_exo_supp.qmd
-      - section: "Partie 5: Introduction aux outils et méthodes à l'état de l'art"
-        contents:
-          - href: content/modern-ds/index.qmd
-            text: "Introduction"
-          - content/modern-ds/continuous_integration.qmd
-          - content/modern-ds/dallE.qmd
-          - content/modern-ds/s3.qmd
-          - content/modern-ds/elastic_approfondissement.qmd
-          - content/modern-ds/elastic_intro.qmd
-      - section: "Git: Un incontournable pour les data scientists"
-        contents:
-          - href: content/git/index.qmd
-            text: "Introduction"
-          - content/git/introgit.qmd
-          - content/git/exogit.qmd
-      - section: "Contenu annexe"
-        contents:
-          - content/annexes/evaluation.qmd
-          - content/annexes/corrections.qmd
-          - href: https://linogaliana.github.io/python-datascientist-slides/#/title-slide
-            text: "Slides de présentation"
+    - id: home
+      title: "Homepage"
+      href: index.qmd
+    - id: introduction 
+      title: "Introduction"
+      #collapse-level: 2
+      contents:
+        - content/getting-started/index.qmd
+        - content/getting-started/01_installation.qmd
+        - content/getting-started/02_DS_environment.qmd
+        - content/getting-started/03_data_analysis.qmd
+        - content/getting-started/04_python_practice.qmd
+        - content/getting-started/05_rappels_types.qmd
+        - content/getting-started/06_rappels_fonctions.qmd
+        - content/getting-started/07_rappels_classes.qmd
+    - id: manipulation 
+      title: "Manipuler"
+      #collapse-level: 2
+      contents:
+        - href: content/manipulation/index.qmd
+          text: "Introduction"
+        - content/manipulation/01_numpy.qmd
+        - content/manipulation/02a_pandas_tutorial.qmd
+        - content/manipulation/02b_pandas_TP.qmd
+        - content/manipulation/03_geopandas_tutorial.qmd
+        - content/manipulation/03_geopandas_TP.qmd
+        - content/manipulation/04a_webscraping_TP.qmd
+        - content/manipulation/04c_API_TP.qmd
+        - content/manipulation/04b_regex_TP.qmd
+        - content/manipulation/07_dask.qmd
+    - id: communication
+      title: "Communiquer"
+      #collapse-level: 2
+      contents:
+        - href: content/visualisation/index.qmd
+          text: "Introduction"
+        - content/visualisation/matplotlib.qmd
+        - content/visualisation/maps.qmd
+    - id: modelisation
+      title: "Modéliser"
+      #collapse-level: 2
+      contents:
+        - href: content/modelisation/index.qmd
+          text: "Introduction"
+        - content/modelisation/0_preprocessing.qmd
+        - content/modelisation/1_modelevaluation.qmd
+        - content/modelisation/2_SVM.qmd
+        - content/modelisation/3_regression.qmd
+        - content/modelisation/4_featureselection.qmd
+        - content/modelisation/5_clustering.qmd
+        - content/modelisation/6_pipeline.qmd
+    - id: modelisation
+      title: "NLP"
+      #collapse-level: 2
+      contents:
+        - href: content/NLP/index.qmd
+          text: "Introduction"
+        - content/NLP/01_intro.qmd
+        - content/NLP/02_exoclean.qmd
+        - content/NLP/03_lda.qmd
+        - content/NLP/04_word2vec.qmd
+        - content/NLP/05_exo_supp.qmd
+    - id: modern
+      title: "Approfondissements"
+      #collapse-level: 2
+      contents:
+        - href: content/modern-ds/index.qmd
+          text: "Introduction"
+        - content/modern-ds/continuous_integration.qmd
+        - content/modern-ds/dallE.qmd
+        - content/modern-ds/s3.qmd
+        - content/modern-ds/elastic_approfondissement.qmd
+        - content/modern-ds/elastic_intro.qmd
+    - id: git
+      title: "Git"
+      #collapse-level: 2
+      contents:
+        - href: content/git/index.qmd
+          text: "Introduction"
+        - content/git/introgit.qmd
+        - content/git/exogit.qmd
+    - id: appendix
+      title: "Annexes"
+      #collapse-level: 2
+      contents:
+        - content/annexes/evaluation.qmd
+        - content/annexes/corrections.qmd
+        - href: https://linogaliana.github.io/python-datascientist-slides/#/title-slide
+          text: "Slides de présentation"
 
 
 

content/manipulation/02b_pandas_TP.qmd

@@ -573,7 +573,7 @@ display(
 print("\npetits emetteurs")
 display(
   filosofi.loc[
-    filosofi['dep'].isin(petit_emetteurs.index), ['NBPERSMENFISC16','MED16']
+    filosofi['dep'].isin(petits_emetteurs.index), ['NBPERSMENFISC16','MED16']
     ].mean()
   )
 # Les petits emetteurs sont en moyenne plus pauvres et moins peuplés que les gros emetteurs

content/visualisation/matplotlib.qmd

@@ -169,7 +169,7 @@ pour reproduire la figure 2 de l'_open data_ parisien
 import pandas as pd
 
 url = "https://minio.lab.sspcloud.fr/projet-formation/diffusion/python-datascientist/bike.csv"
-df = pd.read_csv(url, compression = 'gzip')
+df = pd.read_csv(url)
 ```
 
 ::: {.cell .markdown}