Churn_Predictor.py

app.py

@@ -0,0 +1,195 @@
+import gradio as gr
+import joblib
+import pandas as pd
+
+def example1():
+    
+    model=joblib.load("/Users/shvuuuu/Downloads/Creditfile.pkl")
+    input_model = [[45,1.3,2,0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0,0, 0, 1]]
+    pred=model.predict(input_model)
+    churn = "False"
+    if pred[0] == 1:
+        churn = "He Will Churn"
+    elif pred[0] == 0:
+        churn = "He Will Not Churn"
+    return churn
+
+def example2():
+    
+    model=joblib.load("/Users/shvuuuu/Downloads/Creditfile.pkl")
+    input_model = [[7,0.8,5,0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0,0, 0, 1]]
+    pred=model.predict(input_model)
+    churn = "False"
+    if pred[0] == 0:
+        churn = "She Will Churn"
+    elif pred[0] == 1:
+        churn = "She Will Not Churn"
+    return churn
+
+def example3():
+    
+    model=joblib.load("/Users/shvuuuu/Downloads/Creditfile.pkl")
+    input_model = [[41,2,2,0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0]]
+    pred=model.predict(input_model)
+    churn = "False"
+    if pred[0] == 1:
+        churn = "He Will Churn"
+    elif pred[0] == 0:
+        churn = "He Will Not Churn"
+    return churn
+
+
+def example4():
+    
+    model=joblib.load("/Users/shvuuuu/Downloads/Creditfile.pkl")
+    input_model = [[10,1.1,2,0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0]]
+    pred=model.predict(input_model)
+    churn = "False"
+    if pred[0] == 1:
+        churn = "He Will Churn"
+    elif pred[0] == 0:
+        churn = "He Will Not Churn"
+    return churn
+    
+
+def greet(Total_Transaction, Total_Ct_Chng_Q4_Q1, Total_Relationship_Count, Education=None, Annual_Income=None, Marital_Status=None, Card_Type=None):
+    educ, edud, edug, eduh, edup, eduu, ai0, ai40, ai60, ai80, ai120, msd, msm, mss, ctb, ctg, cts = 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    
+    if Annual_Income == "0k-40k":
+        ai0 = 1
+    elif Annual_Income == "40k-60k":
+        ai40 = 1
+    elif Annual_Income == "60k-80k":
+        ai60 = 1
+    elif Annual_Income == "80k-120k":
+        ai80 = 1
+    elif Annual_Income == "120k+":
+        ai120 = 1
+
+    if Marital_Status == "Single":
+        mss = 1
+    elif Marital_Status == "Married":
+        msm = 1
+    elif Marital_Status == "Divorced":
+        msd = 1
+
+    if Card_Type == "Blue":
+        ctb = 1
+    elif Card_Type == "Gold":
+        ctg = 1
+    elif Card_Type == "Silver":
+        cts = 1
+
+    if Education == "College":
+        educ = 1
+    elif Education == "Doctorate":
+        edud = 1
+    elif Education == "Graduate":
+        edug = 1
+    elif Education == "High-School":
+        eduh = 1
+    elif Education == "Post-Graduate":
+        edup = 1
+    elif Education == "Uneducated":
+        eduu = 1
+        
+    
+    input_model = [[Total_Transaction,Total_Ct_Chng_Q4_Q1,Total_Relationship_Count,educ, edud, edug, eduh, edup, eduu, ai120, ai40, ai60, ai80, ai0, msd, msm, mss,ctb, ctg, cts]]
+    model=joblib.load("/Users/shvuuuu/Downloads/Creditfile.pkl")
+    pred=model.predict(input_model)
+    churn = "False"
+    if pred[0] == 1:
+        churn = "True"
+    elif pred[0] == 0:
+        churn = "Flase"
+    return churn
+    
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column(scale=1,min_width=600):
+            gr.Image("/Users/shvuuuu/Downloads/Untitled design copy.png").style(height='7')
+            Total_Transaction = gr.Slider(0, 200,label="Total Transaction Count")
+            Total_Ct_Chng_Q4_Q1 = gr.Slider(0, 30,label="Transaction Count Q4 vs Q1")
+            Total_Relationship_Count = gr.Slider(0, 20,label="Total Relationship Count")
+            
+        with gr.Column(scale=2,min_width=600):
+            with gr.Row():
+                with gr.Column(scale=1,min_width=300):
+                    Annual_Income = gr.Dropdown(["0k-40k","40k-60k","60k-80k","80k-120K","120k+"],label="Annual Income")
+                with gr.Column(scale=2,min_width=300):
+                    Education = gr.Dropdown(["College","Doctorate","Graduate","High-School","Post-Graduate","Uneducated","Unknown"],label="Education")
+                    
+            with gr.Row():
+                with gr.Column(scale=3,min_width=300):
+                    Marital_Status = gr.Dropdown(["Single","Married","Divorced","Unknown"],label="Marital Status")
+                with gr.Column(scale=4,min_width=300):
+                    Card_Type = gr.Dropdown(["Blue","Silver","Gold"],label="Crad Type")
+            churn = gr.Textbox(value="", label="Churn")
+            btn = gr.Button("PREDICT").style(size = "lg")
+            btn.click(fn=greet, inputs=[Total_Transaction,Total_Ct_Chng_Q4_Q1,Total_Relationship_Count,Education,Annual_Income,Marital_Status,Card_Type], outputs=[churn])
+            gr.Markdown("""# Few Examples Based on Real-World Simulations""")
+            
+    with gr.Row():
+        with gr.Column(scale=1,min_width=300):
+            gr.Image("/Users/shvuuuu/Downloads/Untitled design (1)/1.png")
+            churn1 = gr.Textbox(value="", label="Churn")
+            btn1 = gr.Button("PREDICT").style()
+            exp =1
+            btn1.click(fn=example1, inputs=[], outputs=[churn1])
+            gr.Markdown("""
+            # Corporate Professional!
+            Total Transaction Count - 45\n
+            Transaction Count Q4 vs Q1 - 1.3\n
+            Total Relationship Count - 2\n
+            Annual Income - 40k-60k\n
+            Education - Graduate\n
+            Marital Status - Married\n
+            Card Type - Silver\n
+            """)
+        with gr.Column(scale=2,min_width=300):
+            gr.Image("/Users/shvuuuu/Downloads/Untitled design (1)/4.png")
+            churn2 = gr.Textbox(value="", label="Churn")
+            bt2 = gr.Button("PREDICT").style()
+            bt2.click(fn=example2, inputs=[], outputs=[churn2])
+            gr.Markdown("""
+            # Medical Professional!
+            Total Transaction Count - 7\n
+            Transaction Count Q4 vs Q1 - 0.8\n
+            Total Relationship Count - 5\n
+            Annual Income - 80k-120k\n
+            Education - Doctorate\n
+            Marital Status - Married\n
+            Card Type - Gold\n
+            """)
+        with gr.Column(scale=3,min_width=300):
+            gr.Image("/Users/shvuuuu/Downloads/Untitled design (1)/2.png")
+            churn3 = gr.Textbox(value="", label="Churn")
+            btn3 = gr.Button("PREDICT").style()
+            btn3.click(fn=example3, inputs=[], outputs=[churn3])
+            gr.Markdown("""
+            # Freelance Photographer!
+            Total Transaction Count - 41\n
+            Transaction Count Q4 vs Q1 - 2\n
+            Total Relationship Count - 2\n
+            Annual Income - 0k-40k\n
+            Education - High-School\n
+            Marital Status - Single\n
+            Card Type - Blue\n
+            """)
+        with gr.Column(scale=4,min_width=300):
+            gr.Image("/Users/shvuuuu/Downloads/Untitled design (1)/3.png")
+            churn4 = gr.Textbox(value="", label="Churn")
+            btn4 = gr.Button("PREDICT").style()
+            btn4.click(fn=example4, inputs=[], outputs=[churn4])
+            gr.Markdown("""
+            # Retired Veteran Pensioner!
+            Total Transaction Count - 10\n
+            Transaction Count Q4 vs Q1 - 1.1\n
+            Total Relationship Count - 2\n
+            Annual Income - 80k-120k\n
+            Education - Post-Graduate\n
+            Marital Status - Divorced\n
+            Card Type - GOld\n
+            """)
+
+demo.launch()