Update app.py

app.py

@@ -22,50 +22,58 @@ def main():
             st.write(f"- {column}: {values}")
 
     # Main content
-    st.write("This app predicts employee attrition using a trained CatBoost model.")
+    st.write("Welcome to the Employee Attrition Prediction App!")
+    st.write("This app helps HR practitioners predict employee attrition using a trained CatBoost model.")
+    st.write("Please provide the following information to make a prediction:")
 
-    # Add inputs for user to input data
+    # Define layout with three columns
     col1, col2, col3 = st.columns(3)
 
+    # Column 1
     with col1:
         age = st.slider("Age", min_value=18, max_value=70, value=30)
         distance_from_home = st.slider("Distance From Home", min_value=1, max_value=30, value=10)
-        environment_satisfaction = st.slider("Environment Satisfaction", min_value=1, max_value=4, value=2)
+        environment_satisfaction = st.select_slider("Environment Satisfaction", options=[1, 2, 3, 4], value=2)
         hourly_rate = st.slider("Hourly Rate", min_value=30, max_value=100, value=65)
-        job_involvement = st.slider("Job Involvement", min_value=1, max_value=4, value=2)  # Change to Job Involvement
-    
+        job_involvement = st.select_slider("Job Involvement", options=[1, 2, 3, 4], value=2)
+
+    # Column 2
     with col2:
+        job_level = st.select_slider("Job Level", options=[1, 2, 3, 4, 5], value=3)
+        job_satisfaction = st.select_slider("Job Satisfaction", options=[1, 2, 3, 4], value=2)
         monthly_income = st.slider("Monthly Income", min_value=1000, max_value=20000, value=5000)
         num_companies_worked = st.slider("Number of Companies Worked", min_value=0, max_value=10, value=2)
-        percent_salary_hike = st.slider("Percent Salary Hike", min_value=10, max_value=25, value=15)
-        stock_option_level = st.slider("Stock Option Level", min_value=0, max_value=3, value=1)
-        training_times_last_year = st.slider("Training Times Last Year", min_value=0, max_value=6, value=2)
+        over_time = st.checkbox("Over Time")
 
+    # Column 3
     with col3:
-        work_life_balance = st.slider("Work Life Balance", min_value=1, max_value=4, value=2)
+        percent_salary_hike = st.slider("Percent Salary Hike", min_value=10, max_value=25, value=15)
+        stock_option_level = st.select_slider("Stock Option Level", options=[0, 1, 2, 3], value=1)
+        training_times_last_year = st.slider("Training Times Last Year", min_value=0, max_value=6, value=2)
+        work_life_balance = st.select_slider("Work Life Balance", options=[1, 2, 3, 4], value=2)
         years_since_last_promotion = st.slider("Years Since Last Promotion", min_value=0, max_value=15, value=3)
         years_with_curr_manager = st.slider("Years With Current Manager", min_value=0, max_value=15, value=3)
 
-    over_time = st.checkbox("Over Time")
-
     # Create a DataFrame to hold the user input data
     input_data = pd.DataFrame({
         'Age': [age],
         'DistanceFromHome': [distance_from_home],
         'EnvironmentSatisfaction': [environment_satisfaction],
         'HourlyRate': [hourly_rate],
+        'JobInvolvement': [job_involvement],
+        'JobLevel': [job_level],
         'JobSatisfaction': [job_satisfaction],
         'MonthlyIncome': [monthly_income],
         'NumCompaniesWorked': [num_companies_worked],
+        'OverTime': [over_time],
         'PercentSalaryHike': [percent_salary_hike],
         'StockOptionLevel': [stock_option_level],
         'TrainingTimesLastYear': [training_times_last_year],
         'WorkLifeBalance': [work_life_balance],
         'YearsSinceLastPromotion': [years_since_last_promotion],
-        'YearsWithCurrManager': [years_with_curr_manager],
-        'OverTime': [over_time]
+        'YearsWithCurrManager': [years_with_curr_manager]
     })
-    
+
     # Make predictions
     prediction = model.predict(input_data)
     probability = model.predict_proba(input_data)[:, 1]