Update app.py

app.py

@@ -12,6 +12,8 @@ import base64
 from io import BytesIO
 import sys
 import pydeck as pdk
+from ydata_profiling import ProfileReport
+import streamlit.components.v1 as components
 
 # Print the Python version
 print("Python version")
@@ -203,7 +205,7 @@ filtered_data['Predicted_target'] = predicted_target
 
 
 # Set custom width for columns
-tab1, tab2, tab3, tab4 = st.tabs(["Mapa", "Planilha", "Variáveis", "Inteligência Artificial"])
+tab1, tab2, tab3= st.tabs(["Mapa", "Planilha", "Análise dos Dados"])
 
 with tab1:
     # Define a PyDeck view state for the initial map view
@@ -252,21 +254,7 @@ with tab2:
         download_placeholder = st.empty()
         download_placeholder.markdown(href, unsafe_allow_html=True)
 
-with tab3:    
-    folium_layermap = folium.Map(location=[custom_lat, custom_lon], tiles="Cartodb Positron", zoom_start=14)
-
-    # Add heatmap layers for 'Valor_Urb', 'Valor_Eqp', and 'RENDA'
-    add_heatmap_layer(folium_layermap, filtered_data, 'Valor_Urb', 'RdBu_r')
-    add_heatmap_layer(folium_layermap, filtered_data, 'Valor_Eqp', 'RdBu_r')
-    add_heatmap_layer(folium_layermap, filtered_data, 'RENDA', 'RdBu_r')
-
-    # Add layer control
-    folium.LayerControl().add_to(folium_layermap)
-
-    # Display the map using st_folium
-    st_folium(folium_layermap, width=1200, height=400)
-
-with tab4:
+with tab3:
     k_threshold = 5
 
     # Function to perform bootstrap on the predicted target values
@@ -302,4 +290,8 @@ with tab4:
         st.write(f"Valor médio (Reais/m²) para as características selecionadas: ${mean_value:.2f}$ Reais")
         st.write(f"Os valores podem variar entre ${lower_bound:.2f}$ e ${higher_bound:.2f}$ Reais, dependendo das características dos imóveis.")
     else:
-        st.warning(f"**Dados insuficientes para inferência do valor. Mínimo necessário:** {k_threshold}")
+        st.warning(f"**Dados insuficientes para inferência do valor. Mínimo necessário:** {k_threshold}")
+
+    profile = ProfileReport(filtered_data, title="Pandas Profiling Report", explorative=True)
+    profile_html = profile.to_html()
+    components.html(profile_html, height=500, scrolling=True)