diff --git a/src/assets/dash_clientside.js b/src/assets/dash_clientside.js
index babba1c..2c41e6a 100644
--- a/src/assets/dash_clientside.js
+++ b/src/assets/dash_clientside.js
@@ -11,11 +11,15 @@ window.dash_clientside = Object.assign({}, window.dash_clientside, {
}).bindTooltip(feature.properties.tooltip);
},
clusterToLayer: function (feature, latlng, index, context) {
+ console.log(feature);
+ console.log(index);
+ console.log(context);
+
const count = feature.properties.point_count;
const size = count < 100 ? 30 : count < 1000 ? 40 : 50;
- const color = "#333"; // Default cluster color
+ const color = "#555"; // Default cluster color
const icon = L.divIcon({
- html: `${count}
`,
+ html: `${count}
`,
className: "marker-cluster",
iconSize: L.point(size, size),
});
diff --git a/src/figures.py b/src/figures.py
index 15319b8..a63cab8 100644
--- a/src/figures.py
+++ b/src/figures.py
@@ -430,7 +430,7 @@ def get_geographic_maps(dff: pl.DataFrame) -> list | None:
"""
# Si les données sont trop importantes on utilise une carte chloropleth
- if dff.height > 5000:
+ if dff.height > 50000:
return [
dbc.Col(
dcc.Graph(
@@ -443,21 +443,30 @@ def get_geographic_maps(dff: pl.DataFrame) -> list | None:
]
# Liste des codes départements Outre-Mer
- dom_codes = ["971", "972", "973", "974", "976"]
+ region_codes: list = ["Métropole", "971", "972", "973", "974", "976"]
+ dom_codes = region_codes[1:]
# Couleurs accessibles (Okabe-Ito)
color_acheteur = "#E69F00" # Orange
color_titulaire = "#56B4E9" # Bleu ciel
- regions = {
- "Métropole": dff.filter(~pl.col("acheteur_departement_code").is_in(dom_codes))
- }
+ regions = {}
# Ajout des DOM s'ils ont des données
- for code in dom_codes:
- dff_dom = dff.filter(pl.col("acheteur_departement_code") == code)
- if dff_dom.height > 0:
- name = f"Département {code}"
+ for code in region_codes:
+ if code == "Métropole":
+ dff_region = dff.filter(
+ (
+ ~pl.col("acheteur_departement_code").is_in(dom_codes)
+ | (~pl.col("titulaire_departement_code").is_in(dom_codes))
+ )
+ )
+ else:
+ dff_region = dff.filter(
+ (pl.col("acheteur_departement_code") == code)
+ | (pl.col("titulaire_departement_code") == code)
+ )
+ if dff_region.height > 0:
if code == "971":
name = "Guadeloupe"
elif code == "972":
@@ -468,16 +477,21 @@ def get_geographic_maps(dff: pl.DataFrame) -> list | None:
name = "La Réunion"
elif code == "976":
name = "Mayotte"
- regions[name] = dff_dom
+ elif code == "Métropole":
+ name = "Métropole"
+ else:
+ name = f"Département {code}"
+
+ regions[name] = dff_region
# Region centers for dash-leaflet
region_centers = {
- "Métropole": ([46.6, 2.2], 6),
+ "Métropole": ([46.6, 2.2], 5),
"Guadeloupe": ([16.23, -61.55], 9),
"Martinique": ([14.64, -61.02], 10),
"Guyane": ([3.93, -53.12], 7),
- "La Réunion": ([-21.11, 55.53], 10),
- "Mayotte": ([-12.82, 45.16], 11),
+ "La Réunion": ([-21.11, 55.53], 9),
+ "Mayotte": ([-12.82, 45.16], 10),
}
# JavaScript functions for styling
@@ -487,9 +501,6 @@ def get_geographic_maps(dff: pl.DataFrame) -> list | None:
cols = []
for name, region_df in regions.items():
- # Prepare data for GeoJSON
- marker_dicts = []
-
# Trace Acheteurs
mask_acheteur = (
region_df.select(
@@ -503,9 +514,11 @@ def get_geographic_maps(dff: pl.DataFrame) -> list | None:
)
)
+ acheteurs_marker_dicts = []
+
if mask_acheteur.height > 0:
for row in mask_acheteur.to_dicts():
- marker_dicts.append(
+ acheteurs_marker_dicts.append(
{
"lat": row["acheteur_latitude"],
"lon": row["acheteur_longitude"],
@@ -527,9 +540,11 @@ def get_geographic_maps(dff: pl.DataFrame) -> list | None:
)
)
+ titulaires_marker_dicts = []
+
if mask_titulaire.height > 0:
for row in mask_titulaire.to_dicts():
- marker_dicts.append(
+ titulaires_marker_dicts.append(
{
"lat": row["titulaire_latitude"],
"lon": row["titulaire_longitude"],
@@ -538,10 +553,11 @@ def get_geographic_maps(dff: pl.DataFrame) -> list | None:
}
)
- geojson_data = dlx.dicts_to_geojson(marker_dicts)
+ acheteurs_geojson_data = dlx.dicts_to_geojson(acheteurs_marker_dicts)
+ titulaires_geojson_data = dlx.dicts_to_geojson(titulaires_marker_dicts)
center, zoom = region_centers.get(name, ([46.6, 2.2], 6))
- col_width = 12 if name == "Métropole" else 3
+ col_width = 6 if name == "Métropole" else 3
region_id = name.lower().replace(" ", "-")
cols.append(
dbc.Col(
@@ -551,12 +567,22 @@ def get_geographic_maps(dff: pl.DataFrame) -> list | None:
[
dl.TileLayer(),
dl.GeoJSON(
- data=geojson_data,
+ data=titulaires_geojson_data,
cluster=True,
zoomToBoundsOnClick=True,
pointToLayer=point_to_layer,
clusterToLayer=cluster_to_layer,
- id=f"geojson-{region_id}",
+ id=f"geojson-{region_id}-titulaires",
+ options={"fillColor": color_titulaire},
+ ),
+ dl.GeoJSON(
+ data=acheteurs_geojson_data,
+ cluster=True,
+ zoomToBoundsOnClick=True,
+ pointToLayer=point_to_layer,
+ clusterToLayer=cluster_to_layer,
+ id=f"geojson-{region_id}-acheteurs",
+ options={"fillColor": color_acheteur},
),
],
center=center,
diff --git a/src/pages/statistiques.py b/src/pages/statistiques.py
index 1a74231..99fcbc7 100644
--- a/src/pages/statistiques.py
+++ b/src/pages/statistiques.py
@@ -163,6 +163,7 @@ def udpate_dashboard_cards(
total_montant = df_per_uid.select(pl.col("montant").sum()).item()
nb_marches = df_per_uid.height
+ # À transformer en fonction
card_basic_counts = [
html.P(["Nombre de marchés : ", html.Strong(str(format_number(nb_marches)))]),
html.P(