Application file

.gitignore

@@ -0,0 +1,5 @@
+.env
+.ipynb_checkpoints/
+venv/
+
+

app.py

@@ -0,0 +1,117 @@
+import gradio as gr
+import pandas as pd
+import joblib
+
+# Load your churn prediction model
+model = joblib.load('best_model.pkl')
+
+# Create a Gradio interface
+def predict_churn(SeniorCitizen, Partner, Dependents, tenure, InternetService,
+                  OnlineSecurity, OnlineBackup, DeviceProtection, TechSupport,
+                  StreamingTV, StreamingMovies, Contract, PaperlessBilling,
+                  PaymentMethod, MonthlyCharges, TotalCharges):
+    
+    # Create a dictionary with input features
+    input_data = {
+        'SeniorCitizen': SeniorCitizen,
+        'Partner': Partner,
+        'Dependents': Dependents,
+        'tenure': tenure,
+        'InternetService': InternetService,
+        'OnlineSecurity': OnlineSecurity,
+        'OnlineBackup': OnlineBackup,
+        'DeviceProtection': DeviceProtection,
+        'TechSupport': TechSupport,
+        'StreamingTV': StreamingTV,
+        'StreamingMovies': StreamingMovies,
+        'Contract': Contract,
+        'PaperlessBilling': PaperlessBilling,
+        'PaymentMethod': PaymentMethod,
+        'MonthlyCharges': MonthlyCharges,
+        'TotalCharges': TotalCharges
+    }
+    
+    # Create a DataFrame from the input data
+    input_df = pd.DataFrame([input_data])
+    
+    # Make predictions
+    prediction = model.predict(input_df)
+    
+    
+    # Determine the churn prediction
+    if prediction[0] == 0:
+        churn_result = '<span style="color: limegreen;font-size:20px;">Customer will not churn</span>'
+    else:
+        churn_result = '<span style="color: red;font-size:20px;">Customer will churn</span>'
+    
+    return churn_result
+
+# Define Gradio components
+with gr.Blocks(theme=gr.themes.Base(primary_hue="stone",neutral_hue="stone")) as block:
+    gr.Markdown(
+        """# 👋 Welcome to Team Cape Cod's Churn Prediction App
+
+                This App predicts whether a customer will churn or not""")
+    
+    with gr.Row():
+        with gr.Column():
+            SeniorCitizen = gr.Radio(["Yes", "No"], label="Are you a Senior Citizen?")
+            Partner = gr.Radio(["Yes", "No"], label="Do you have a partner?")
+            Dependents = gr.Radio(["Yes", "No"], label="Do you have dependents?")
+            tenure = gr.Number(label="Tenure (months): How long have you been at the company")
+            InternetService = gr.Radio(["DSL", "Fiber optic", "No"], label="What Internet Service Do You Use?")
+            OnlineSecurity = gr.Radio(["Yes", "No", "No internet service"], label="Do You Have Online Security?")
+            
+        with gr.Column():
+            OnlineBackup = gr.Radio(["Yes", "No", "No internet service"], label="Do You Have Any Online Backup Service?")
+            DeviceProtection = gr.Radio(["Yes", "No", "No internet service"], label="Do You Use Any Device Protection?")
+            TechSupport = gr.Radio(["Yes", "No", "No internet service"], label="Do You Use TechSupport?")
+            StreamingTV = gr.Radio(["Yes", "No", "No internet service"], label="Do You Stream TV?")
+            StreamingMovies = gr.Radio(["Yes", "No", "No internet service"], label="Do You Stream Movies?")
+            
+        with gr.Column():
+            Contract = gr.Radio(["Month-to-month", "One year", "Two year"], label="What Is Your Contract Type?")
+            PaperlessBilling = gr.Radio(["Yes", "No"], label="Do You Use Paperless Billing?")
+            PaymentMethod = gr.Dropdown(["Electronic check", "Mailed check", "Bank transfer (automatic)", "Credit card (automatic)"], label="What Payment Method Do You Use?")
+            MonthlyCharges = gr.Number(label="What is your Monthly Charge?")
+            TotalCharges = gr.Number(label="What are your Total Charges?")
+            
+
+            #create a variable that clear button will clear
+            input_components = [SeniorCitizen, Partner, Dependents, tenure,
+                                InternetService, OnlineSecurity, OnlineBackup, DeviceProtection,
+                                TechSupport, StreamingTV, StreamingMovies, Contract, PaperlessBilling,
+                                PaymentMethod, MonthlyCharges, TotalCharges]
+            
+             #Create a button user will click to clear inputs selected
+            gr.ClearButton(input_components)           
+    
+    #create markdown for ouput
+    text = gr.Markdown("## Churn Status")
+    
+    # Define Gradio outputs
+    output = gr.HTML("Awaiting Prediction")
+
+    # Create a button
+    button = gr.Button("Predict")
+
+    # Create Gradio interface
+    button.click(fn=predict_churn,inputs=input_components, outputs=output)
+    
+    #create an example dataframe
+    gr.Markdown("## Input Examples")
+
+    gr.Examples([['No', 'No', 'No', '12', 'Fiber optic', 'No', 'No', 'No', 'No', 'Yes', 'No', 'Month-to-month', 'Yes', 'Electronic check', '84.45', '1059.55'],
+                 
+                      ['No', 'No', 'No', '9', 'No', 'No internet service', 'No internet service', 'No internet service', 'No internet service', 'No internet service', 'No internet service', 'Month-to-month', 'No', 'Mailed check', '20.40', '181.80'],
+                      
+                      ['No', 'No', 'No', '27', 'DSL', 'Yes', 'No', 'Yes', 'Yes', 'Yes', 'Yes', 'One year', 'No', 'Electronic check', '81.70', '2212.55']],
+                      
+                      inputs=input_components)
+
+#start gradio app
+block.launch(
+    auth=("azubiafrica", "teamcapecod"),
+    auth_message="Enter the username 'azubiafrica' and password 'teamcapecod' for this demo app"
+)
+

best_model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:09bdc833b302834fb10202f3baa4ea24b159082c3d3d08b7acf7e8217d878bf1
+size 8707

requirements.txt

@@ -0,0 +1,5 @@
+gradio==3.45.2
+joblib==1.2.0
+numpy==1.24.3
+pandas==2.0.2
+scikit-learn==1.2.2