Add one map

.github/workflows/documentation.yml

@@ -61,16 +61,18 @@ jobs:
         env:
           CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
 
-      - name: Install
-        run: python setup.py install
+      # - name: Install
+      #   run: python setup.py install
 
       - name: Copy license
         run: cp LICENSE* ./_doc
       - name: Copy changelogs
         run: cp CHANGELOGS* ./_doc
 
       - name: Documentation
-        run: python -m sphinx ./_doc ./dist/html -n -w doc.txt
+        run: |
+          export PYTHONPATH=.
+          python -m sphinx ./_doc ./dist/html -n -w doc.txt
 
       - name: Summary
         run: cat doc.txt

CHANGELOGS.rst

@@ -4,6 +4,7 @@ Change Logs
 0.4.0
 +++++
 
+* :pr:`55`: add one map
 * :pr:`54`: add content for machine learning
 * :pr:`47`: add helpers to create a video
 

_doc/api/datasets.rst

@@ -2,10 +2,15 @@
 Jeux de données
 ===============
 
+Cartographie
+============
+
+.. autofunction:: teachpyx.datasets.load_enedis_dataset
+
 Classification
 ==============
 
-.. autofunction:: teachpyx.datasets.wines.load_wines_dataset
+.. autofunction:: teachpyx.datasets.load_wines_dataset
 
 Outils
 ======

_doc/c_data/graphes.rst

@@ -0,0 +1,8 @@
+=======
+Graphes
+=======
+
+.. toctree::
+    :maxdepth: 2
+
+    enedis_cartes

_doc/c_data/index.rst

@@ -19,3 +19,4 @@ pour la manipulations de données avec les *DataFrames*.
 
     matrices
     dataframes
+    graphes

_doc/c_data/nb_dataframe.ipynb

@@ -6168,18 +6168,6 @@
    "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.12"
   }
  },
  "nbformat": 4,

_doc/c_ml/rappel.rst

@@ -527,10 +527,8 @@ en :epkg:`R`.
 Dessiner des cartes
 ===================
 
-.. toctree::
-    :maxdepth: 1
+Voir :ref:`Tracer une carte <nbl-c_data-enedis_cartes>`.
 
-    notebooks/enedis_cartes
 
 Exercices
 =========
@@ -547,6 +545,4 @@ Si tous ces rappels vous sont connus, vous devriez être prêt
 * `Challenges algorithmiques <http://www.xavierdupre.fr/app/ensae_projects/helpsphinx/index.html#challenges>`_
 
 Un dernier lien vers des exercices dont les questions sont plus détaillées et
-corrigées :
-
-* `exercices corrigés <http://www.xavierdupre.fr/app/ensae_teaching_cs/helpsphinx/questions/exams_1A.html#seances-notees>`_
+corrigées :ref:`l-examens-notes`.

_doc/conf.py

@@ -386,6 +386,7 @@
 epkg_dictionary.update(
     {
         "csv": "https://fr.wikipedia.org/wiki/Comma-separated_values",
+        "Enedis": "https://data.enedis.fr/",
         "fonction": "https://fr.wikipedia.org/wiki/Fonction_(math%C3%A9matiques)",
         "fonction continue": "https://fr.wikipedia.org/wiki/Continuit%C3%A9_(math%C3%A9matiques)",
         "machine learning": "https://en.wikipedia.org/wiki/Machine_learning",

_doc/notebook_gallery.rst

@@ -118,6 +118,7 @@ Data
     c_data/nb_dataframe
     c_data/nb_numpy
     c_data/nb_pandas
+    c_data/enedis_cartes
 
 Correction d'examens
 ====================
@@ -155,5 +156,5 @@ Machine Learning
 .. nblinkgallery::
     :caption: machine learning
 
-    practice/ml/wines_color
-    practice/ml/wines_reg
+    practice/ml/winesc_color
+    practice/ml/winesr_reg

_doc/practice/exams.rst

@@ -5,6 +5,8 @@ Exercices minutés
 Ces exercices ont été proposés pour examens d'évaluation.
 Il est recommandé de savoir les faire en moins de deux heures.
 
+.. _l-examens-notes:
+
 Séances notées
 ==============
 

_doc/practice/index_ml.rst

@@ -13,10 +13,10 @@ Machine Learning
     :maxdepth: 1
     :caption: Régression
 
-    ml/wines_reg
+    ml/winesr_reg
 
 .. toctree::
     :maxdepth: 1
     :caption: Classification
 
-    ml/wines_color
+    ml/winesc_color

_doc/practice/ml/wines_color.ipynb → _doc/practice/ml/winesc_color.ipynb

@@ -1254,18 +1254,6 @@
    "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.12"
   }
  },
  "nbformat": 4,

_unittests/ut_datasets/test_documentation.py

@@ -10,6 +10,12 @@ def test_documentation_wines(self):
         self.assertIn("<nbl-", links[0])
         self.assertIn("wines", links[0])
 
+    def test_documentation_enedis(self):
+        links = list_notebooks_rst_links("c_data", "enedis")
+        self.assertNotEmpty(links)
+        self.assertIn("<nbl-c_data", links[0])
+        self.assertIn("enedis", links[0])
+
     def _test_documentation_movie(self):
         links = list_notebooks_rst_links("ml", "movielens")
         self.assertNotEmpty(links)

_unittests/ut_datasets/test_enedis.py

@@ -0,0 +1,13 @@
+import unittest
+from teachpyx.ext_test_case import ExtTestCase
+from teachpyx.datasets import load_enedis_dataset
+
+
+class TestEnedis(ExtTestCase):
+    def test_enedis(self):
+        df = load_enedis_dataset()
+        self.assertEqual(df.shape, (9719, 26))
+
+
+if __name__ == "__main__":
+    unittest.main()

requirements-dev.txt

@@ -1,13 +1,15 @@
 black
 black-nb
 blockdiag
+cartopy
 chardet
 cloudpickle
 coverage
 cytoolz
 dbfread
 dict2xml
 furo
+geopandas
 ipython
 jinja2
 jupyter

teachpyx/datasets/__init__.py

@@ -3,7 +3,8 @@
 # from .carreau import load_carreau_from_zip
 # from .dummies import line2d
 # from .duration import duration_selling
-# from .enedis import load_enedis_dataset
+from .enedis import load_enedis_dataset
+
 # from .geojson import get_geojson_countries
 # from .graph import create_tiny_graph
 # from .movies import load_movielens_dataset

teachpyx/datasets/documentation.py

@@ -4,9 +4,11 @@
 from typing import List, Optional
 
 
-def root() -> str:
+def root(subfolder: str) -> str:
     "Returns the local folder for all notebooks."
     this = os.path.dirname(__file__)
+    if subfolder == "c_data":
+        return os.path.abspath(os.path.normpath(os.path.join(this, "..", "..", "_doc")))
     return os.path.abspath(
         os.path.normpath(os.path.join(this, "..", "..", "_doc", "practice"))
     )
@@ -23,7 +25,7 @@ def list_notebooks(
     :param contains: extrait à chercher
     :return: liste des notebooks (sans répertoire)
     """
-    nbs = [os.path.join(root(), subfolder)]
+    nbs = [os.path.join(root(subfolder), subfolder)]
     nb_ = list(filter(os.path.exists, nbs))
     assert len(nb_) > 0, "Unable to find notebooks in\n{0}".format("\n".join(nbs))
     nb = nb_[0]
@@ -33,7 +35,12 @@ def list_notebooks(
         names = [_ for _ in os.listdir(nb) if _.startswith(name_)]
     if contains is not None:
         names = [_ for _ in os.listdir(nb) if contains in _]
-    assert len(names) > 0, f"Unable to find any notebook in '{nb}'."
+    assert len(names) > 0, (
+        f"Unable to find any notebook in {nb!r} "
+        f"(this file is {__file__}, "
+        f"root is {root(subfolder)}, "
+        f"sub is {subfolder!r}, name is {name!r})."
+    )
     return names
 
 
@@ -54,8 +61,11 @@ def _name(s):
 
     def _title(sub, s):
         reg = re.compile("# (.+)")
-        fn = os.path.join(root(), sub, s)
-        assert os.path.exists(fn), f"Unable to find filename {fn!r}."
+        fn = os.path.join(root(sub), sub, s)
+        assert os.path.exists(fn), (
+            f"Unable to find filename {fn!r} (this file is {__file__}, "
+            f"root is {root(sub)!r}, sub is {sub!r}, name is {name!r})."
+        )
         with open(fn, "r", encoding="utf-8") as f:
             content = f.read()
         f = reg.findall(content)
@@ -64,7 +74,8 @@ def _title(sub, s):
         return title
 
     names = list_notebooks(subfolder, name, contains)
+    prefix = "" if subfolder == "c_data" else "practice-"
     return [
-        f":ref:`{_title(subfolder, name)} <nbl-practice-{subfolder}-{_name(name)}>`"
+        f":ref:`{_title(subfolder, name)} <nbl-{prefix}{subfolder}-{_name(name)}>`"
         for name in names
     ]

teachpyx/datasets/enedis.py

@@ -0,0 +1,30 @@
+# coding: utf-8
+import pandas
+
+
+def load_enedis_dataset() -> pandas.DataFrame:
+    """
+    Retourne des données extraites du site :epkg:`Enedis` :
+    `Production électrique annuelle par filière à la maille commune
+    <https://data.enedis.fr/explore/dataset/production-electrique-par-filiere-a-la-maille-commune/export/>`_.
+    Le jeu proposé est un extrait pour les années 2015-2016.
+    Notebooks associés à ce jeu de données :
+
+    .. runpython::
+        :rst:
+
+        from teachpyx.datasets.documentation import list_notebooks_rst_links
+        links = list_notebooks_rst_links("c_data", "enedis")
+        links = ["    * %s" % s for s in links]
+        print("\\n".join(links))
+
+    :return: :epkg:`pandas:DataFrame`
+    """
+    url = (
+        "https://github.com/sdpython/teachdata/raw/main/enedis/"
+        "production-electrique-par-filiere-a-la-maille-commune.extrait.2015-2016.csv.zip"
+    )
+    df = pandas.read_csv(url, sep=";", encoding="utf-8")
+    df["long"] = df["Geo Point 2D"].apply(lambda x: float(x.split(",")[1].strip()))
+    df["lat"] = df["Geo Point 2D"].apply(lambda x: float(x.split(",")[0].strip()))
+    return df

teachpyx/datasets/wines.py

@@ -1,6 +1,6 @@
 import os
-import pandas
 from numpy.random import permutation
+import pandas
 from .data_helper import get_data_folder
 
 
@@ -19,7 +19,7 @@ def load_wines_dataset(
         :rst:
 
         from teachpyx.datasets.documentation import list_notebooks_rst_links
-        links = list_notebooks_rst_links("ml", "wines")
+        links = list_notebooks_rst_links("ml", "winesr")
         links = ["    * %s" % s for s in links]
         print("\\n".join(links))
 
@@ -58,14 +58,14 @@ def load_wine_dataset(
     .. runpython::
         :rst:
 
-        from papierstat.datasets.documentation import list_notebooks_rst_links
-        links = list_notebooks_rst_links("ml", "linreg")
+        from teachpyx.datasets.documentation import list_notebooks_rst_links
+        links = list_notebooks_rst_links("ml", "winesc")
         links = ["    * %s" % s for s in links]
         print("\\n".join(links))
 
     :param download: télécharge le jeu de données ou considères une copie en local.
     :param shuffle: permute aléatoire les données (elles ne le sont pas)
-    :return: :class:`pandas:DataFrame`
+    :return: :class:`pandas.DataFrame`
     """
     if download:
         url = "https://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data"