Grid de cards avec points de rupture #65

data/departements.json

@@ -391,8 +391,16 @@
     "departement": "La Réunion",
     "region": "La Réunion"
   },
+  "975": {
+    "departement": "Saint-Pierre-et-Miquelon",
+    "region": "Saint-Pierre-et-Miquelon"
+  },
   "976": {
     "departement": "Mayotte",
     "region": "Mayotte"
+  },
+  "977": {
+    "departement": "Saint-Barthelemy",
+    "region": "Saint-Barthelemy"
   }
 }

src/figures.py

@@ -417,18 +417,12 @@ def get_geographic_maps(dff: pl.DataFrame) -> list | None:
         },
     }
 
-    # Liste des codes départements Outre-Mer
-    dom_codes = [code for code in regions.keys() if code != "Métropole"]
-    print("dom codes", dom_codes)
-
     def make_map_data(region_code: str) -> tuple[list, str or None]:
         lff: pl.LazyFrame = dff.lazy()
         if region_code == "Métropole":
             lff = lff.filter(
-                (
-                    ~pl.col("acheteur_departement_code").is_in(dom_codes)
-                    | (~pl.col("titulaire_departement_code").is_in(dom_codes))
-                )
+                (pl.col("acheteur_departement_code").str.len_chars() == 2)
+                & (pl.col("titulaire_departement_code").str.len_chars() == 2)
             )
         else:
             lff = lff.filter(
@@ -436,14 +430,14 @@ def get_geographic_maps(dff: pl.DataFrame) -> list | None:
                 | (pl.col("titulaire_departement_code") == code)
             )
 
-        nb_marches = lff.select("uid").group_by("uid").first().collect().height
+        nb_marches = lff.select("uid").collect()["uid"].n_unique()
 
         if nb_marches == 0:
             return [], None
 
         dfs = []
 
-        if (code == "Métropole" and nb_marches > 20000) or (
+        if (code == "Métropole" and nb_marches > 30000) or (
             code != "Métropole" and nb_marches > 10000
         ):
             _map_type: str = "chloropleth"
@@ -505,10 +499,9 @@ def get_geographic_maps(dff: pl.DataFrame) -> list | None:
 
     for code in regions.keys():
         regions[code]["data"], map_type = make_map_data(code)
-        print("region", regions[code]["name"], len(regions[code]["data"][0]), map_type)
 
         if map_type == "chloropleth":
-            map_graph = make_chloropleth_map(regions[code])  # call chloropleth function
+            map_graph = make_chloropleth_map(regions[code])
         elif map_type == "clusters":
             map_graph = make_clusters_map(regions[code])
         elif map_type is None:
@@ -516,15 +509,9 @@ def get_geographic_maps(dff: pl.DataFrame) -> list | None:
         else:
             raise ValueError(f"Map type '{map_type}' not recognised")
 
-        col = dbc.Col(
-            children=[
-                html.H5(regions[code]["name"]),
-                map_graph,
-            ],
-            md=6 if code == "Métropole" else 3,
-            width=12,
-            className="mb-4",
-        )
+        md = 6 if code == "Métropole" else 3
+
+        col = make_card(regions[code]["name"], md=md, fig=map_graph)
         cols.append(col)
 
     return cols
@@ -543,7 +530,6 @@ def make_chloropleth_map(region: dict) -> dcc.Graph:
         range_color=(df_map["uid"].min(), df_map["uid"].max()),
         labels={"uid": "Marchés attribués"},
         scope="europe",
-        width=400,
         height=400,
     )
 
@@ -561,7 +547,7 @@ def make_chloropleth_map(region: dict) -> dcc.Graph:
     return graph
 
 
-def make_clusters_map(region: dict):
+def make_clusters_map(region: dict) -> dl.Map:
     # JavaScript functions for styling
     ns = Namespace("dash_clientside", "leaflet")
     point_to_layer = ns("pointToLayer")
@@ -615,6 +601,31 @@ def make_clusters_map(region: dict):
     return leaflet_map
 
 
+def make_card(
+    title: str, subtitle=None, fig=None, paragraphs=None, md=3, width=12
+) -> dbc.Col:
+    children = []
+    if title:
+        children.append(html.H5(title, className="card-title"))
+    if subtitle:
+        children.append(html.H6(subtitle, className="card-subtitle mb-2 text-muted"))
+    if fig:
+        children.append(fig)
+    if paragraphs:
+        for p in paragraphs:
+            p.className = "card-text"
+            children.append(p)
+
+    card = dbc.Col(
+        html.Div(html.Div(className="card-body", children=children), className="card"),
+        lg=6,
+        xl=4,
+        # width=width,
+        # className="mb-4",
+    )
+    return card
+
+
 def make_column_picker(page: str):
     table_data = []
     table_columns = [

src/pages/statistiques.py

@@ -5,9 +5,7 @@ import polars as pl
 import polars.selectors as cs
 from dash import Input, Output, callback, dcc, html, register_page
 
-from src.figures import (
-    get_geographic_maps,
-)
+from src.figures import get_geographic_maps, make_card
 from src.utils import (
     departements,
     df,
@@ -52,8 +50,8 @@ layout = [
                     dbc.Row(
                         [
                             dbc.Col(
-                                width=12,
-                                md=3,
+                                xl=3,
+                                lg=4,
                                 id="filters",
                                 children=[
                                     html.H5("Période d'attribution"),
@@ -87,22 +85,10 @@ layout = [
                             ),
                             dbc.Col(
                                 width=12,
-                                md=9,
+                                lg=8,
+                                xl=9,
                                 id="cards",
-                                children=[
-                                    dbc.Row(
-                                        (
-                                            dbc.Col(
-                                                width=6,
-                                                md=4,
-                                                className="card",
-                                                id="card_basic_counts",
-                                            )
-                                        ),
-                                        className="mb-4",
-                                    ),
-                                    dbc.Row(id="maps_row"),
-                                ],
+                                children=[],
                             ),
                         ]
                     )
@@ -114,8 +100,7 @@ layout = [
 
 
 @callback(
-    Output("card_basic_counts", "children"),
-    Output("maps_row", "children"),
+    Output("cards", "children"),
     Input("dashboard_year", "value"),
     Input("dashboard_acheteur_categorie", "value"),
     Input("dashboard_acheteur_departement_code", "value"),
@@ -163,6 +148,8 @@ def udpate_dashboard_cards(
     total_montant = df_per_uid.select(pl.col("montant").sum()).item()
     nb_marches = df_per_uid.height
 
+    cards = []
+
     # À transformer en fonction
     card_basic_counts = [
         html.P(["Nombre de marchés : ", html.Strong(str(format_number(nb_marches)))]),
@@ -175,6 +162,8 @@ def udpate_dashboard_cards(
         html.P(["Montant total : ", html.Strong(format_number(total_montant) + " €")]),
     ]
 
-    geographic_maps = get_geographic_maps(dff)
+    cards.append(make_card(title="Résumé", paragraphs=card_basic_counts))
 
-    return card_basic_counts, geographic_maps
+    geographic_maps: list[dbc.Col] = get_geographic_maps(dff)
+
+    return dbc.Row(children=cards + geographic_maps)