Ajoute l’étape 25 de répartition des minifigs par genre

lib/plots/gender_palette.py

@@ -0,0 +1,14 @@
+"""Palette de couleurs et libellés pour les genres des personnages."""
+
+GENDER_COLORS = {
+    "male": "#4c72b0",
+    "female": "#c44e52",
+    "unknown": "#7f7f7f",
+}
+
+GENDER_LABELS = {
+    "male": "Homme",
+    "female": "Femme",
+    "unknown": "Inconnu",
+    "": "Inconnu",
+}

lib/plots/minifig_character_spans.py

@@ -8,22 +8,10 @@ from matplotlib.patches import Patch
 
 from lib.filesystem import ensure_parent_dir
 from lib.milestones import load_milestones
+from lib.plots.gender_palette import GENDER_COLORS, GENDER_LABELS
 from lib.rebrickable.stats import read_rows
 
 
-GENDER_COLORS = {
-    "male": "#4c72b0",
-    "female": "#c44e52",
-    "unknown": "#7f7f7f",
-}
-GENDER_LABELS = {
-    "male": "Homme",
-    "female": "Femme",
-    "unknown": "Inconnu",
-    "": "Inconnu",
-}
-
-
 def load_spans(path: Path) -> List[dict]:
     """Charge le CSV des bornes min/max par personnage."""
     return read_rows(path)

lib/plots/minifig_characters.py

@@ -7,22 +7,10 @@ import matplotlib.pyplot as plt
 from matplotlib.patches import Patch
 
 from lib.filesystem import ensure_parent_dir
+from lib.plots.gender_palette import GENDER_COLORS, GENDER_LABELS
 from lib.rebrickable.stats import read_rows
 
 
-GENDER_COLORS = {
-    "male": "#4c72b0",
-    "female": "#c44e52",
-    "unknown": "#7f7f7f",
-}
-GENDER_LABELS = {
-    "male": "Homme",
-    "female": "Femme",
-    "unknown": "Inconnu",
-    "": "Inconnu",
-}
-
-
 def load_counts(path: Path) -> List[dict]:
     """Charge le CSV des comptes par personnage."""
     return read_rows(path)

lib/plots/minifig_gender_share.py

@@ -0,0 +1,48 @@
+"""Diagramme de répartition des minifigs par genre."""
+
+from pathlib import Path
+from typing import List
+
+import matplotlib.pyplot as plt
+
+from lib.filesystem import ensure_parent_dir
+from lib.plots.gender_palette import GENDER_COLORS, GENDER_LABELS
+from lib.rebrickable.stats import read_rows
+
+
+def load_gender_counts(path: Path) -> List[dict]:
+    """Charge le CSV des comptes par genre."""
+    return read_rows(path)
+
+
+def plot_minifig_gender_share(counts_path: Path, destination_path: Path) -> None:
+    """Trace un diagramme circulaire de la répartition des minifigs par genre."""
+    rows = load_gender_counts(counts_path)
+    if not rows:
+        return
+    genders = [row["gender"] for row in rows]
+    counts = [int(row["minifig_count"]) for row in rows]
+    colors = [GENDER_COLORS.get(gender.strip().lower(), GENDER_COLORS["unknown"]) for gender in genders]
+    total = sum(counts)
+    labels = []
+    for gender, count in zip(genders, counts):
+        percent = (count / total) * 100 if total else 0
+        label = f"{GENDER_LABELS.get(gender.strip().lower(), 'Inconnu')} ({percent:.1f} %)"
+        labels.append(label)
+
+    fig, ax = plt.subplots(figsize=(6, 6))
+    ax.pie(
+        counts,
+        labels=labels,
+        colors=colors,
+        startangle=90,
+        wedgeprops={"linewidth": 0.6, "edgecolor": "#0d0d0d"},
+    )
+    centre_circle = plt.Circle((0, 0), 0.5, fc="white")
+    ax.add_artist(centre_circle)
+    ax.set_title("Répartition des minifigs par genre (thèmes filtrés)")
+
+    ensure_parent_dir(destination_path)
+    fig.tight_layout()
+    fig.savefig(destination_path, dpi=160)
+    plt.close(fig)

lib/rebrickable/minifig_characters.py

@@ -34,6 +34,28 @@ def aggregate_by_character(rows: Iterable[dict]) -> List[dict]:
     return aggregates
 
 
+def aggregate_by_gender(rows: Iterable[dict]) -> List[dict]:
+    """Compte les minifigs distinctes par genre (fig_num unique)."""
+    genders_by_fig: Dict[str, str] = {}
+    counts: Dict[str, int] = defaultdict(int)
+    for row in rows:
+        fig_num = row["fig_num"].strip()
+        gender = row.get("gender", "").strip().lower()
+        normalized = gender if gender in ("male", "female") else "unknown"
+        if fig_num == "":
+            continue
+        if fig_num in genders_by_fig:
+            continue
+        genders_by_fig[fig_num] = normalized
+        counts[normalized] += 1
+    aggregates: List[dict] = []
+    ordered = ["female", "male", "unknown"]
+    for gender in ordered:
+        if gender in counts:
+            aggregates.append({"gender": gender, "minifig_count": str(counts[gender])})
+    return aggregates
+
+
 def write_character_counts(path: Path, rows: Sequence[dict]) -> None:
     """Écrit le CSV des comptes par personnage."""
     ensure_parent_dir(path)
@@ -45,6 +67,17 @@ def write_character_counts(path: Path, rows: Sequence[dict]) -> None:
             writer.writerow(row)
 
 
+def write_gender_counts(path: Path, rows: Sequence[dict]) -> None:
+    """Écrit le CSV des comptes par genre."""
+    ensure_parent_dir(path)
+    fieldnames = ["gender", "minifig_count"]
+    with path.open("w", newline="") as csv_file:
+        writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
+        writer.writeheader()
+        for row in rows:
+            writer.writerow(row)
+
+
 def load_sets_enriched(path: Path) -> Dict[str, str]:
     """Indexe les années par set_num."""
     lookup: Dict[str, str] = {}