Update app.py

app.py

@@ -159,7 +159,6 @@ st.markdown(
         h1, h2, h3, h4, h5, h6 {
             color: #00f7ff !important; /* Headings to cyan */
         }
-
         /* Styles for loader */
         .loader {
             border: 5px solid #f3f3f3;
@@ -169,7 +168,6 @@ st.markdown(
             height: 30px;
             animation: spin 2s linear infinite;
         }
-
         @keyframes spin {
             0% { transform: rotate(0deg); }
             100% { transform: rotate(360deg); }
@@ -279,7 +277,8 @@ def animated_progress_bar(progress_var, message="Processing..."):
         time.sleep(0.01) # reduced sleep timer as its getting too long
 
 # --- Main App Logic ---
-if app_mode == "Data Upload":
+
+if app_mode == "Data Upload": #Check
     st.title("📤 Data Upload & Analysis")
 
     uploaded_file = st.file_uploader("Upload Dataset", type=["csv", "xlsx"])
@@ -305,7 +304,7 @@ if app_mode == "Data Upload":
                     pr = generate_profile(df)
                     st_profile_report(pr)
 
-elif app_mode == "Smart Cleaning":
+elif app_mode == "Smart Cleaning": #Check
     st.title("🧼 Intelligent Data Cleaning")
 
     if st.session_state.raw_data is not None:
@@ -414,7 +413,7 @@ elif app_mode == "Smart Cleaning":
         with col2:
             st.write("Cleaned Data", df.head(3))
 
-elif app_mode == "Advanced EDA":
+elif app_mode == "Advanced EDA": #Check
     st.title("🔍 Advanced Exploratory Analysis")
 
     if st.session_state.cleaned_data is not None:
@@ -476,7 +475,7 @@ elif app_mode == "Advanced EDA":
             except Exception as e:
                 st.error(f"Error generating plot: {e}")
 
-elif app_mode == "Model Training":
+elif app_mode == "Model Training": #Check
     st.title("🤖 Model Training Studio")
 
     if st.session_state.cleaned_data is not None:
@@ -647,8 +646,8 @@ elif app_mode == "Model Training":
                 except Exception as e:
                     st.error(f"Error during training: {e}")
 
-# Predictions Section
-elif app_mode == "Predictions":
+#Predictions
+elif app_mode == "Predictions": #Check
     st.title("🔮 Make Predictions")
 
     if st.session_state.model is not None and st.session_state.preprocessor is not None:
@@ -665,6 +664,7 @@ elif app_mode == "Predictions":
 
         if st.button("Predict"):
             try:
+
                 input_df = pd.DataFrame([input_data])
                 # Preprocess input
                 input_processed = preprocessor.transform(input_df)
@@ -684,9 +684,8 @@ elif app_mode == "Predictions":
                 st.error(f"Error during prediction: {e}")
     else:
         st.warning("Please train a model first.")
-
-
-    elif app_mode == "Visualization Lab":
+        
+elif app_mode == "Visualization Lab":
     st.title("📊 Advanced Visualization Lab")
 
     if st.session_state.cleaned_data is not None: