Update app.py

app.py

@@ -407,6 +407,12 @@ elif app_mode == "Data Cleaning":
         st.warning("Please upload data first")
         st.stop()  # Stop execution if no data uploaded
 
+    if 'cleaned_data' in st.session_state and st.session_state.cleaned_data is not None:
+        df = st.session_state.cleaned_data.copy()  # Work on the latest cleaned data
+    else:
+        st.warning("No cleaned data available. Please clean your data first.")
+        st.stop()  # Stop execution if no cleaned data is available
+
 
     # Data Health Dashboard
     enhance_section_title("Data Health Dashboard", "📊")
@@ -575,8 +581,11 @@ elif app_mode == "EDA":
         st.warning("Please upload data first")
         st.stop()  # Stop execution if no data uploaded
 
-    df = st.session_state.cleaned_data.copy()  # Work on the latest cleaned data
-    # Rest of the EDA code...
+    if 'cleaned_data' in st.session_state and st.session_state.cleaned_data is not None:
+        df = st.session_state.cleaned_data.copy()  # Work on the latest cleaned data
+    else:
+        st.warning("No cleaned data available. Please clean your data first.")
+        st.stop() 
 
 
     # --------------------------
@@ -910,7 +919,12 @@ elif app_mode == "Model Training":
         st.warning("Please upload data first")
         st.stop()  # Stop execution if no data uploaded
 
-    df = st.session_state.cleaned_data.copy()  # Work on the latest cleaned data
+    if 'cleaned_data' in st.session_state and st.session_state.cleaned_data is not None:
+        df = st.session_state.cleaned_data.copy()  # Work on the latest cleaned data
+    else:
+        st.warning("No cleaned data available. Please clean your data first.")
+        st.stop()  # Stop execution if no cleaned data is available
+
     # Rest of the model training code...
 
 
@@ -1093,12 +1107,21 @@ elif app_mode == "Model Training":
                     st.metric("R2", f"{validation_metrics['r2']:.2f}")
 
 # Predictions Section (Fixed)
-if app_mode == "Predictions":
-    st.title("🔮 Predictive Analytics - Informed Business Decisions")
+elif app_mode == "Predictions":
+    st.title("🔮 Predictive Analytics")
+
+    if st.session_state.raw_data is None:
+        st.warning("Please upload data first")
+        st.stop()  # Stop execution if no data uploaded
+
+    if 'cleaned_data' in st.session_state and st.session_state.cleaned_data is not None:
+        df = st.session_state.cleaned_data.copy()  # Work on the latest cleaned data
+    else:
+        st.warning("No cleaned data available. Please clean your data first.")
+        st.stop()  # Stop execution if no cleaned data is available
+
+    # Rest of the predictions code...
 
-    if st.session_state.get("model") is None:
-        st.warning("Please train a model first")
-        st.stop()
 
     model_data = st.session_state.model  # Get the entire dictionary
     model = model_data['model']  # Access model