Update app.py

app.py

@@ -177,33 +177,34 @@ if st.session_state.df is not None:
                     fig = px.box(st.session_state.df, x="job_title", y="salary_in_usd",
                                  title="Salary Distribution by Job Title")
 
-                    # Insert visualization after "5. Company Size"
-                    insert_section = "5. Company Size"
+                    # Insert visualization after "4. Geographic Salary Variations" for better context
+                    insert_section = "4. Geographic Salary Variations"
                     if insert_section in result:
-                        # Split the report at the "Company Size" section
                         parts = result.split(insert_section)
-                        st.markdown(parts[0])  # Display everything before "Company Size"
-                        st.markdown(f"## {insert_section}{parts[1].split('6.')[0]}")  # Show the "Company Size" content
-                        
+                        st.markdown(parts[0])  # Show content before section
+                        st.markdown(f"## {insert_section}{parts[1].split('5.')[0]}")  # Show the section content
+
                         # Insert the visualization here
                         st.plotly_chart(fig, use_container_width=True)
 
                         # Continue with the rest of the report
-                        st.markdown("## 6." + parts[1].split("6.")[1])  # Display everything after "Company Size"
+                        st.markdown("## 5." + parts[1].split("5.")[1])
                     else:
-                        # If "Company Size" not found, show full report and plot at the end
+                        # Default behavior if the section isn't found
                         st.markdown(result)
                         st.plotly_chart(fig, use_container_width=True)
                 else:
                     st.markdown(result)
 
-    # Tab 2: Full Data Visualization
+    # Tab 2: Enhanced Full Data Visualization
     with tab2:
         st.subheader("📊 Comprehensive Data Visualizations")
 
+        # Histogram of job titles
         fig1 = px.histogram(st.session_state.df, x="job_title", title="Job Title Frequency")
         st.plotly_chart(fig1)
 
+        # Bar chart of average salary by experience level
         fig2 = px.bar(
             st.session_state.df.groupby("experience_level")["salary_in_usd"].mean().reset_index(),
             x="experience_level", y="salary_in_usd",
@@ -211,10 +212,22 @@ if st.session_state.df is not None:
         )
         st.plotly_chart(fig2)
 
+        # New Visualization: Salary by Employment Type
+        fig3 = px.box(st.session_state.df, x="employment_type", y="salary_in_usd",
+                      title="Salary Distribution by Employment Type")
+        st.plotly_chart(fig3)
+
+        # New Visualization: Salary by Company Size (if available)
+        if "company_size" in st.session_state.df.columns:
+            fig4 = px.box(st.session_state.df, x="company_size", y="salary_in_usd",
+                          title="Salary Distribution by Company Size")
+            st.plotly_chart(fig4)
+
     temp_dir.cleanup()
 else:
     st.info("Please load a dataset to proceed.")
 
+# Sidebar Reference
 with st.sidebar:
     st.header("📚 Reference:")
     st.markdown("[SQL Agents w CrewAI & Llama 3 - Plaban Nayak](https://github.com/plaban1981/Agents/blob/main/SQL_Agents_with_CrewAI_and_Llama_3.ipynb)")