Update app.py

app.py

@@ -62,19 +62,44 @@ def run_acquisition_analysis(
 
     if analysis_type == "Mix Analysis":
 
-        result = calculate_vintage_mix(
-            df=acq,
-            vintage_col="booking_vintage",
-            group_col=dimension
+        result = (
+            acq.groupby(
+                ["booking_vintage", dimension]
+            )
+            .agg(
+                count=("account_id", "nunique"),
+                balance=("credit_limit", "sum")
+            )
+            .reset_index()
         )
 
+        vintage_total = (
+            result.groupby("booking_vintage")["count"]
+            .transform("sum")
+        )
+
+        result["rate"] = (
+            result["count"] / vintage_total
+        ) * 100
+
+        result["rate"] = result["rate"].round(2)
+
         result = result.rename(
             columns={
-                "accounts": "count"
+                "booking_vintage": "vintage",
+                dimension: "segment"
             }
         )
 
-        return result
+        return result[
+            [
+                "vintage",
+                "segment",
+                "count",
+                "balance",
+                "rate"
+            ]
+        ]
 
     # ----------------------------------------
     # LIMIT ANALYSIS
@@ -93,9 +118,36 @@ def run_acquisition_analysis(
             .reset_index()
         )
 
-        return result
+        vintage_total = (
+            result.groupby("booking_vintage")["balance"]
+            .transform("sum")
+        )
+
+        result["rate"] = (
+            result["balance"] / vintage_total
+        ) * 100
+
+        result["rate"] = result["rate"].round(2)
+
+        result = result.rename(
+            columns={
+                "booking_vintage": "vintage",
+                dimension: "segment"
+            }
+        )
+
+        return result[
+            [
+                "vintage",
+                "segment",
+                "count",
+                "balance",
+                "rate"
+            ]
+        ]
 
     else:
+
         return pd.DataFrame()
 
 
@@ -136,7 +188,7 @@ def run_performance_analysis(
     )
 
     # ----------------------------------------
-    # STANDARDIZED OUTPUT FORMAT
+    # IDENTIFY METRIC COLUMN
     # ----------------------------------------
 
     metric_col = [
@@ -144,6 +196,10 @@ def run_performance_analysis(
         if "rate" in col.lower()
     ][0]
 
+    # ----------------------------------------
+    # STANDARDIZED OUTPUT
+    # ----------------------------------------
+
     if group_col is not None:
 
         final_result = result.rename(
@@ -163,20 +219,43 @@ def run_performance_analysis(
 
         final_result["segment"] = "Overall"
 
-    # Add dummy balance column for consistency
-    # Later replace with actual exposure logic
+    # ----------------------------------------
+    # BALANCE LOGIC
+    # ----------------------------------------
 
-    final_result["balance"] = None
+    # Delinquency metrics
+    if metric_name in [
+        "30+@3",
+        "30+@6",
+        "60+@6"
+    ]:
 
-    final_result = final_result[
-        [
-            "booking_vintage",
-            "segment",
-            "total_accounts",
-            "balance",
-            "rate"
-        ]
-    ]
+        if "bad_balance" in final_result.columns:
+
+            final_result["balance"] = (
+                final_result["bad_balance"]
+            )
+
+        else:
+
+            final_result["balance"] = None
+
+    # NCL metric
+    elif metric_name == "Yr1 NCL":
+
+        if "total_balance" in final_result.columns:
+
+            final_result["balance"] = (
+                final_result["total_balance"]
+            )
+
+        else:
+
+            final_result["balance"] = None
+
+    # ----------------------------------------
+    # FINAL OUTPUT FORMAT
+    # ----------------------------------------
 
     final_result = final_result.rename(
         columns={
@@ -185,7 +264,23 @@ def run_performance_analysis(
         }
     )
 
-    return final_result
+    required_cols = [
+        "vintage",
+        "segment",
+        "count",
+        "balance",
+        "rate"
+    ]
+
+    for col in required_cols:
+
+        if col not in final_result.columns:
+
+            final_result[col] = None
+
+    return final_result[
+        required_cols
+    ]
 
 
 # ---------------------------------------------------
@@ -196,6 +291,10 @@ def update_analysis_dropdown(
     dataset_type
 ):
 
+    # ----------------------------------------
+    # ACQUISITION
+    # ----------------------------------------
+
     if dataset_type == "Acquisition":
 
         return gr.update(
@@ -206,6 +305,10 @@ def update_analysis_dropdown(
             value="Mix Analysis"
         )
 
+    # ----------------------------------------
+    # PERFORMANCE
+    # ----------------------------------------
+
     elif dataset_type == "Performance":
 
         return gr.update(
@@ -223,6 +326,10 @@ def update_dimension_dropdown(
     dataset_type
 ):
 
+    # ----------------------------------------
+    # ACQUISITION
+    # ----------------------------------------
+
     if dataset_type == "Acquisition":
 
         return gr.update(
@@ -235,6 +342,10 @@ def update_dimension_dropdown(
             value="sourcing_channel"
         )
 
+    # ----------------------------------------
+    # PERFORMANCE
+    # ----------------------------------------
+
     elif dataset_type == "Performance":
 
         return gr.update(
@@ -308,12 +419,22 @@ with gr.Blocks() as app:
         )
 
         analysis_selection = gr.Dropdown(
-            choices=[],
+            choices=[
+                "Mix Analysis",
+                "Limit Analysis"
+            ],
+            value="Mix Analysis",
             label="Analysis"
         )
 
         dimension_selection = gr.Dropdown(
-            choices=[],
+            choices=[
+                "sourcing_channel",
+                "fico_band",
+                "city_tier",
+                "occupation_type"
+            ],
+            value="sourcing_channel",
             label="Dimension"
         )