add conclusion

app.py

@@ -354,7 +354,7 @@ def main():
     
 
     st.markdown("""
-    ### Introduction to the Traffic Accident Dataset
+    # Introduction to the Traffic Accident Dataset
     This dataset contains detailed information about traffic accidents in the city of **Tempe**. It includes various attributes of the accidents, such as the severity of injuries, the demographics of the drivers involved, the locations of the incidents, and the conditions at the time of the accidents. The dataset covers accidents that occurred over several years, with data on factors like **weather conditions**, **road surface conditions**, the **time of day**, and the type of **violations** (e.g., alcohol or drug use) that may have contributed to the accident.
     
     The data was sourced from **Tempe City's traffic incident reports** and provides a comprehensive view of the factors influencing road safety and accident severity in the city. By analyzing this dataset, we can gain insights into the key contributors to traffic incidents and uncover trends that could help improve traffic safety measures, urban planning, and law enforcement policies in the city.
@@ -597,7 +597,7 @@ def main():
     st.markdown("---")
     
     # Add TODO section title
-    st.markdown("## To-Do List for Part 3")
+    st.markdown("# To-Do List for Part 3")
     st.markdown("For the final project part 3, we plan to create two pairs of linked interactive visualizations for analyzing traffic accident data as follows:")
     
     # Create two columns
@@ -642,7 +642,49 @@ def main():
             - Clear interaction instructions
             - Display of applied filters
         """)
-
+    st.markdown("---")
+    
+    # Add conclusion section
+    st.markdown("# FP2 Conclusion")
+    
+    st.markdown("""
+    In FP2, we created interactive visualizations to analyze traffic accident data, focusing on trends, contributing factors, and safety implications. 
+    Each visualization provides specific insights and helps users make data-driven decisions to improve road safety.
+    """)
+    
+    # Create columns for different visualizations' conclusions
+    con1, con2, con3 = st.columns(3)
+    
+    with con1:
+        st.markdown("""
+        ### Crash Trend Over Time
+        An interactive line chart showing annual crash patterns with an optional weather filter, helping identify:
+        * Long-term accident trends
+        * Weather-related correlations
+        * Seasonal patterns in crash frequencies
+        * Peak accident periods
+        """)
+    
+    with con2:
+        st.markdown("""
+        ### Severity of Violations Across Age Groups
+        Visualizes crash severities by violation types and driver age groups:
+        * Age-specific violation patterns
+        * High-risk behavior identification
+        * Severity distribution analysis
+        * Targeted intervention opportunities
+        """)
+    
+    with con3:
+        st.markdown("""
+        ### Distribution of Incidents
+        A comprehensive analysis of incidents by various factors:
+        * Collision manner analysis
+        * Surface condition impacts
+        * Gender-based patterns
+        * Environmental factor effects
+        * Time-based distribution
+        """)
 
 
 if __name__ == "__main__":