Feat: visualisation des Competences et des themes dans students

recopytex/dashboard/student_analysis/app.py

@@ -18,10 +18,19 @@ from ...config import NO_ST_COLUMNS
 from ..app import app
 from ...scripts.exam import Exam
 
+
 def get_students(csv):
     return list(pd.read_csv(csv).T.to_dict().values())
 
 
+COLORS = {
+    ".": "black",
+    0: "#E7472B",
+    1: "#FF712B",
+    2: "#F2EC4C",
+    3: "#68D42F",
+}
+
 QUESTION_COLUMNS = [
     {"id": "id", "name": "Question"},
     {
@@ -119,9 +128,6 @@ layout = html.Div(
                             ),
                             id="eval-table",
                         ),
-                        html.Div(
-                            id="describe",
-                        ),
                     ],
                     id="Évaluations",
                 ),
@@ -131,7 +137,7 @@ layout = html.Div(
                             id="competences-viz",
                         ),
                         html.Div(
-                            id="themes-viz",
+                            id="themes-vizz",
                         ),
                     ],
                     id="visualisation",
@@ -213,5 +219,85 @@ def update_exam_scores(data):
     scores = pp_q_scores(scores)
     assessment_scores = scores.groupby(["Nom"]).agg({"Note": "sum", "Bareme": "sum"})
     return [assessment_scores.reset_index().to_dict("records")]
-    return [{}]
+
+
+@app.callback(
+        [
+            dash.dependencies.Output("competences-viz", "children"),
+            ],
+        [
+            dash.dependencies.Input("student-scores", "data"),
+            ],
+        )
+def update_competences_viz(data):
+    scores = pd.DataFrame.from_records(data)
+    scores = pp_q_scores(scores)
+    pt = pd.pivot_table(
+        scores,
+        index=["Competence"],
+        columns="Score",
+        aggfunc="size",
+        fill_value=0,
+    )
+    fig = go.Figure()
+    bars = [
+        {"score": -1, "name": "Pas de réponse", "color": COLORS["."]},
+        {"score": 0, "name": "Faux", "color": COLORS[0]},
+        {"score": 1, "name": "Peu juste", "color": COLORS[1]},
+        {"score": 2, "name": "Presque juste", "color": COLORS[2]},
+        {"score": 3, "name": "Juste", "color": COLORS[3]},
+    ]
+    for b in bars:
+        try:
+            fig.add_bar(
+                x=list(config["competences"].keys()), y=pt[b["score"]], name=b["name"], marker_color=b["color"]
+            )
+        except KeyError:
+            pass
+    fig.update_layout(barmode="relative")
+    fig.update_layout(
+        height=500,
+        margin=dict(l=5, r=5, b=5, t=5),
+    )
+    return [dcc.Graph(figure=fig)]
+
+@app.callback(
+        [
+            dash.dependencies.Output("themes-vizz", "children"),
+            ],
+        [
+            dash.dependencies.Input("student-scores", "data"),
+            ],
+        )
+def update_themes_viz(data):
+    scores = pd.DataFrame.from_records(data)
+    scores = pp_q_scores(scores)
+    pt = pd.pivot_table(
+        scores,
+        index=["Domaine"],
+        columns="Score",
+        aggfunc="size",
+        fill_value=0,
+    )
+    fig = go.Figure()
+    bars = [
+        {"score": -1, "name": "Pas de réponse", "color": COLORS["."]},
+        {"score": 0, "name": "Faux", "color": COLORS[0]},
+        {"score": 1, "name": "Peu juste", "color": COLORS[1]},
+        {"score": 2, "name": "Presque juste", "color": COLORS[2]},
+        {"score": 3, "name": "Juste", "color": COLORS[3]},
+    ]
+    for b in bars:
+        try:
+            fig.add_bar(
+                x=list(pt.index), y=pt[b["score"]], name=b["name"], marker_color=b["color"]
+            )
+        except KeyError:
+            pass
+    fig.update_layout(barmode="relative")
+    fig.update_layout(
+        height=500,
+        margin=dict(l=5, r=5, b=5, t=5),
+    )
+    return [dcc.Graph(figure=fig)]