Update app.py

app.py

@@ -3,21 +3,26 @@
 import pandas as pd
 import gradio as gr
 
-from helper.vintage_helpers import (
+from helpers.vintage_helpers import (
     create_booking_vintage
 )
 
-from helper.data_merger import (
+from helpers.data_merger import (
     merge_acq_perf
 )
 
+from metrics.mix_metrics import (
+    calculate_vintage_mix,
+    calculate_limit_mix
+)
+
 from analytics.performance_analysis import (
     generate_metric_view
 )
 
-# -----------------------------------
+# ---------------------------------------------------
 # LOAD DATA
-# -----------------------------------
+# ---------------------------------------------------
 
 acq = pd.read_csv(
     "data/acquisition.csv"
@@ -27,26 +32,78 @@ perf = pd.read_csv(
     "data/performance.csv"
 )
 
-# -----------------------------------
+# ---------------------------------------------------
 # CREATE VINTAGE
-# -----------------------------------
+# ---------------------------------------------------
 
 acq = create_booking_vintage(acq)
 
-# -----------------------------------
+# ---------------------------------------------------
 # MERGE DATA
-# -----------------------------------
+# ---------------------------------------------------
 
 master_df = merge_acq_perf(
     acq,
     perf
 )
 
-# -----------------------------------
-# MAIN ANALYTICS ENGINE
-# -----------------------------------
+# ---------------------------------------------------
+# ACQUISITION ANALYSIS ENGINE
+# ---------------------------------------------------
 
-def run_analysis(
+def run_acquisition_analysis(
+    analysis_type,
+    dimension
+):
+
+    # ----------------------------------------
+    # MIX ANALYSIS
+    # ----------------------------------------
+
+    if analysis_type == "Mix Analysis":
+
+        result = calculate_vintage_mix(
+            df=acq,
+            vintage_col="booking_vintage",
+            group_col=dimension
+        )
+
+        result = result.rename(
+            columns={
+                "accounts": "count"
+            }
+        )
+
+        return result
+
+    # ----------------------------------------
+    # LIMIT ANALYSIS
+    # ----------------------------------------
+
+    elif analysis_type == "Limit Analysis":
+
+        result = (
+            acq.groupby(
+                ["booking_vintage", dimension]
+            )
+            .agg(
+                count=("account_id", "nunique"),
+                balance=("credit_limit", "sum")
+            )
+            .reset_index()
+        )
+
+        return result
+
+    else:
+        return pd.DataFrame()
+
+
+# ---------------------------------------------------
+# PERFORMANCE ANALYSIS ENGINE
+# ---------------------------------------------------
+
+def run_performance_analysis(
     metric_name,
     portfolio_view
 ):
@@ -78,32 +135,109 @@ def run_analysis(
         group_col=group_col
     )
 
-    return result
+    # ----------------------------------------
+    # STANDARDIZED OUTPUT FORMAT
+    # ----------------------------------------
 
-# -----------------------------------
-# GRADIO UI
-# -----------------------------------
+    metric_col = [
+        col for col in result.columns
+        if "rate" in col.lower()
+    ][0]
 
-with gr.Blocks() as app:
+    if group_col is not None:
 
-    gr.Markdown(
-        "# Risk Analytics Manager Agent"
+        final_result = result.rename(
+            columns={
+                group_col: "segment",
+                metric_col: "rate"
+            }
+        )
+
+    else:
+
+        final_result = result.rename(
+            columns={
+                metric_col: "rate"
+            }
+        )
+
+        final_result["segment"] = "Overall"
+
+    # Add dummy balance column for consistency
+    # Later replace with actual exposure logic
+
+    final_result["balance"] = None
+
+    final_result = final_result[
+        [
+            "booking_vintage",
+            "segment",
+            "total_accounts",
+            "balance",
+            "rate"
+        ]
+    ]
+
+    final_result = final_result.rename(
+        columns={
+            "booking_vintage": "vintage",
+            "total_accounts": "count"
+        }
     )
 
-    with gr.Row():
+    return final_result
+
 
-        metric_name = gr.Dropdown(
+# ---------------------------------------------------
+# DYNAMIC DROPDOWN LOGIC
+# ---------------------------------------------------
+
+def update_analysis_dropdown(
+    dataset_type
+):
+
+    if dataset_type == "Acquisition":
+
+        return gr.update(
+            choices=[
+                "Mix Analysis",
+                "Limit Analysis"
+            ],
+            value="Mix Analysis"
+        )
+
+    elif dataset_type == "Performance":
+
+        return gr.update(
             choices=[
                 "30+@3",
                 "30+@6",
                 "60+@6",
                 "Yr1 NCL"
             ],
-            value="30+@6",
-            label="Metric"
+            value="30+@6"
+        )
+
+
+def update_dimension_dropdown(
+    dataset_type
+):
+
+    if dataset_type == "Acquisition":
+
+        return gr.update(
+            choices=[
+                "sourcing_channel",
+                "fico_band",
+                "city_tier",
+                "occupation_type"
+            ],
+            value="sourcing_channel"
         )
 
-        portfolio_view = gr.Dropdown(
+    elif dataset_type == "Performance":
+
+        return gr.update(
             choices=[
                 "Overall",
                 "Channel",
@@ -111,10 +245,98 @@ with gr.Blocks() as app:
                 "City Tier",
                 "Occupation"
             ],
-            value="Overall",
-            label="Portfolio View"
+            value="Overall"
+        )
+
+
+# ---------------------------------------------------
+# MASTER ROUTER
+# ---------------------------------------------------
+
+def run_analysis(
+    dataset_type,
+    analysis_selection,
+    dimension_selection
+):
+
+    # ----------------------------------------
+    # ACQUISITION ANALYSIS
+    # ----------------------------------------
+
+    if dataset_type == "Acquisition":
+
+        return run_acquisition_analysis(
+            analysis_type=analysis_selection,
+            dimension=dimension_selection
+        )
+
+    # ----------------------------------------
+    # PERFORMANCE ANALYSIS
+    # ----------------------------------------
+
+    elif dataset_type == "Performance":
+
+        return run_performance_analysis(
+            metric_name=analysis_selection,
+            portfolio_view=dimension_selection
         )
 
+    else:
+
+        return pd.DataFrame()
+
+
+# ---------------------------------------------------
+# GRADIO UI
+# ---------------------------------------------------
+
+with gr.Blocks() as app:
+
+    gr.Markdown(
+        "# Risk Analytics Manager Agent"
+    )
+
+    with gr.Row():
+
+        dataset_type = gr.Dropdown(
+            choices=[
+                "Acquisition",
+                "Performance"
+            ],
+            value="Acquisition",
+            label="Dataset"
+        )
+
+        analysis_selection = gr.Dropdown(
+            choices=[],
+            label="Analysis"
+        )
+
+        dimension_selection = gr.Dropdown(
+            choices=[],
+            label="Dimension"
+        )
+
+    # ----------------------------------------
+    # DYNAMIC DROPDOWNS
+    # ----------------------------------------
+
+    dataset_type.change(
+        fn=update_analysis_dropdown,
+        inputs=dataset_type,
+        outputs=analysis_selection
+    )
+
+    dataset_type.change(
+        fn=update_dimension_dropdown,
+        inputs=dataset_type,
+        outputs=dimension_selection
+    )
+
+    # ----------------------------------------
+    # RUN BUTTON
+    # ----------------------------------------
+
     run_button = gr.Button(
         "Run Analysis"
     )
@@ -124,8 +346,9 @@ with gr.Blocks() as app:
     run_button.click(
         fn=run_analysis,
         inputs=[
-            metric_name,
-            portfolio_view
+            dataset_type,
+            analysis_selection,
+            dimension_selection
         ],
         outputs=output_table
     )