split consumer groups best character

03_quant_report.py

@@ -174,6 +174,11 @@ def _(data_validated):
     return (data,)
 
 
+@app.cell
+def _():
+    return
+
+
 @app.cell
 def _():
     # Check if all business owners are missing a 'Consumer type' in demographics
@@ -404,6 +409,37 @@ def _():
     return
 
 
+@app.cell
+def _():
+    mo.md(r"""
+    ## Character Ranking Points (per customer segment)
+    """)
+    return
+
+
+@app.cell
+def _(S, data):
+    _content = ""
+    for _consumer_group, _consumer_df in utils.split_consumer_groups(data).items():
+
+        _char_rank = S.get_character_ranking(_consumer_df)[0]
+        _char_rank_weighted = calculate_weighted_ranking_scores(_char_rank)
+
+        _plot = S.plot_weighted_ranking_score(
+            _char_rank_weighted, 
+            title=f'Most Popular Character - Weighted Popularity Score - CONSUMER: "{_consumer_group.replace()}"<br>(1st=3pts, 2nd=2pts, 3rd=1pt)',
+            x_label='Voice'
+        )
+
+        _content += f"""
+        {mo.ui.altair_chart(_plot)}
+    
+        """
+
+    mo.md(_content)
+    return
+
+
 @app.cell(hide_code=True)
 def _():
     mo.md(r"""
@@ -579,7 +615,6 @@ def _(S, voice_1_10):
     {mo.ui.altair_chart(_summary)}
     """)
 
-
     return