Update src/streamlit_app.py

src/streamlit_app.py

@@ -32,8 +32,8 @@ if menu == "Train Model":
         st.pyplot(fig)
 
     st.subheader("Model Training")
-    # target_column = st.selectbox("Select Target Column", options=data.columns, index=data.columns.get_loc('churn') if 'churn' in data.columns else 0)
-    # feature_columns = st.multiselect("Select Feature Columns", options=[col for col in data.columns if col != target_column])
+    target_column = st.selectbox("Select Target Column", options=data.columns, index=data.columns.get_loc('churn') if 'churn' in data.columns else 0)
+    feature_columns = st.multiselect("Select Feature Columns", options=[col for col in data.columns if col != target_column])
 
     #if feature_columns and target_column:
         # X = pd.get_dummies(data[feature_columns])
@@ -43,11 +43,11 @@ if menu == "Train Model":
     # Automatically exclude identifier columns
     # exclude_columns = ['Customer', 'Policy', 'Policy Number', 'Response']
     # feature_columns = [col for col in data.columns if col not in exclude_columns]
-    target_column = 'Response'
+    # target_column = 'Response'
 
-    feature_columns = data.drop(columns=[target_column]).select_dtypes(include=[np.number]).columns.tolist()
+    # feature_columns = data.drop(columns=[target_column]).select_dtypes(include=[np.number]).columns.tolist()
     X= data[feature_columns]
-    y = data['Response']
+    y = data[target_column]
 
 
     X = data.drop('Response', axis = 1)