Update src/dashboard_app.py

src/dashboard_app.py

@@ -162,6 +162,7 @@ def load_data(source_type, source_value, header_param, sep=None, db_config=None)
         st.session_state.data_loaded_id = data_id
         st.session_state.last_header_preference = (header_param == 0)
         st.sidebar.success("Données chargées avec succès.")
+        st.info("Les données chargées sont disponibles sous le nom `data` pour les requêtes SQL.") # Added line
         st.rerun()
     else:
         st.session_state.dataframe_to_export = None
@@ -242,6 +243,28 @@ app_tab, manual_tab, chat_tab, schedule_tab = st.tabs([
 # ONGLET APPLICATION PRINCIPALE
 # ==============================================================================
 with app_tab:
+    st.markdown("""
+        <style>
+        /* Increase font size for dataframe cells */
+        .stDataFrame div[data-testid="stDataframeData"] div {
+            font-size: 1.2em !important;
+        }
+        /* Increase font size for Plotly chart text (labels, tooltips, etc.) */
+        .js-plotly-plot .plotly .modebar,
+        .js-plotly-plot .plotly .cursor-pointer,
+        .js-plotly-plot .plotly .legendtext,
+        .js-plotly-plot .plotly .xtick,
+        .js-plotly-plot .plotly .ytick,
+        .js-plotly-plot .plotly .annotation-text,
+        .js-plotly-plot .plotly .gtext {
+            font-size: 1.2em !important;
+        }
+        /* Increase font size for table headers */
+        .stDataFrame div[data-testid="stDataframeHeaders"] div {
+             font-size: 1.2em !important;
+        }
+        </style>
+        """, unsafe_allow_html=True)
     with st.sidebar:
         st.header("⚙️ Configuration")
 
@@ -549,7 +572,7 @@ with app_tab:
         if columns_defined:
             st.subheader("🛠️ Construire les Analyses")
             st.write("Ajoutez des blocs d'analyse pour explorer vos données.")
-            col_add1, col_add2, col_add3 = st.columns(3)
+            col_add1, col_add2, col_add3, col_add4 = st.columns(4) # Added col_add4
             analysis_key_suffix = st.session_state.data_loaded_id or "data_loaded"
             with col_add1:
                 if st.button("➕ Tableau Agrégé", key=f"add_agg_{analysis_key_suffix}", help="Stats groupées (ex: moyenne par catégorie)."):
@@ -566,6 +589,11 @@ with app_tab:
                     new_id = max([a.get('id', -1) for a in st.session_state.analyses] + [-1]) + 1
                     st.session_state.analyses.append({'type': 'descriptive_stats', 'params': {}, 'result': None, 'id': new_id, 'executed_params': None})
                     st.rerun()
+            with col_add4: # Added new button
+                if st.button("➕ Requête SQL", key=f"add_sql_{analysis_key_suffix}", help="Exécuter une requête SQL sur les données chargées."):
+                    new_id = max([a.get('id', -1) for a in st.session_state.analyses] + [-1]) + 1
+                    st.session_state.analyses.append({'type': 'sql_query', 'params': {'query': ''}, 'result': None, 'id': new_id, 'executed_params': None})
+                    st.rerun()
         else:
              st.warning("Impossible de définir les types de colonnes. Vérifiez les données ou l'erreur de chargement. Section Analyse désactivée.")
 
@@ -816,6 +844,12 @@ with app_tab:
                                     selected_size = st.selectbox(f"Taille (Opt., Num.):", map_options_num_orig, index=get_safe_index(map_options_num_orig, analysis['params'].get('size_column')), key=f"graph_size_{analysis_id}", disabled=size_disabled, format_func=lambda x: x if x is not None else "Aucune")
                                     st.session_state.analyses[i]['params']['size_column'] = selected_size
 
+                                # Add a text input for the chart title
+                                init_analysis_state(i, 'chart_title', '') # Initialize state for title
+                                chart_title_input = st.text_input("Titre du graphique (Opt.):", value=analysis['params'].get('chart_title', ''), key=f"graph_title_{analysis_id}")
+                                st.session_state.analyses[i]['params']['chart_title'] = chart_title_input
+
+
                                 # --- Facet, Hover & Autres ---
                                 col1_extra, col2_extra = st.columns(2)
                                 with col1_extra:
@@ -930,15 +964,21 @@ with app_tab:
                                             if final_value and graph_analysis_type in ['sunburst', 'treemap']: px_args['values'] = final_value
                                             if final_gantt_end and graph_analysis_type == 'timeline': px_args['x_end'] = final_gantt_end; px_args['x_start'] = final_x # x_start est la colonne X
 
-                                            title_parts = [graph_analysis_type.title()] # Construire titre
-                                            if final_y and graph_analysis_type not in ['histogram', 'pie', 'radar', 'scatter_matrix', 'sunburst', 'treemap']: title_parts.append(f"{final_y} vs")
-                                            elif graph_analysis_type == 'pie' and final_value: title_parts.append(f"{final_value} par") # Utiliser value pour pie
-                                            elif graph_analysis_type == 'radar' and final_y: title_parts.append(f"{final_y} pour") # Utiliser Y (r) pour radar
+                                            # --- Set Title ---
+                                            final_chart_title = current_params.get('chart_title', '') # Retrieve the chart title
+                                            if final_chart_title:
+                                                px_args['title'] = final_chart_title
+                                            else:
+                                                # Keep the auto-generated title if no custom title is provided
+                                                title_parts = [graph_analysis_type.title()]
+                                                if final_y and graph_analysis_type not in ['histogram', 'pie', 'radar', 'scatter_matrix', 'sunburst', 'treemap']: title_parts.append(f"{final_y} vs")
+                                                elif graph_analysis_type == 'pie' and final_value: title_parts.append(f"{final_value} par")
+                                                elif graph_analysis_type == 'radar' and final_y: title_parts.append(f"{final_y} pour")
+                                                if final_x: title_parts.append(final_x)
+                                                if final_color: title_parts.append(f"par {final_color}")
+                                                if is_aggregated: title_parts.append("(Agrégé)")
+                                                px_args['title'] = " ".join(title_parts)
 
-                                            if final_x: title_parts.append(final_x)
-                                            if final_color: title_parts.append(f"par {final_color}")
-                                            if is_aggregated: title_parts.append("(Agrégé)")
-                                            px_args['title'] = " ".join(title_parts)
 
                                             # --- Génération Plotly ---
                                             try:
@@ -1066,7 +1106,94 @@ with app_tab:
                         analysis_type_display = st.session_state.analyses[i]['type'] # Renamed to avoid conflict
                         try:
                             if analysis_type_display in ['aggregated_table', 'descriptive_stats'] and isinstance(result_data, pd.DataFrame):
-                                st.dataframe(result_data.T if analysis_type_display == 'descriptive_stats' else result_data, use_container_width=True)
+                                if analysis_type_display == 'aggregated_table':
+                                    # Apply formatting to aggregated table
+                                    # Identify numerical columns in the aggregated result
+                                    agg_numerical_cols = result_data.select_dtypes(include=np.number).columns.tolist()
+                                    format_dict = {col: '{:,.2f}' for col in agg_numerical_cols} # Example: format numerical columns to 2 decimal places with comma separator
+                                    st.dataframe(result_data.style.format(format_dict), use_container_width=True)
+                                else: # descriptive_stats
+                                    st.dataframe(result_data.T, use_container_width=True)
+                            elif analysis_type_display == 'graph' and isinstance(result_data, go.Figure):
+                                st.plotly_chart(result_data, use_container_width=True)
+                            else: st.write("Résultat non standard:"); st.write(result_data)
+                        except Exception as e_display_result: st.error(f"Erreur affichage résultat {i+1}: {e_display_result}")
+                    elif executed_params_display is not None: # Si on a exécuté mais pas de résultat
+                                                 st.warning(f"L'exécution précédente de l'Analyse {i+1} a échoué ou n'a produit aucun résultat.", icon="⚠️")
+
+                    # ===========================
+                    # Bloc Requête SQL
+                    # ===========================
+                    elif analysis['type'] == 'sql_query':
+                        st.markdown("##### Configuration Requête SQL")
+                        st.info("Exécutez une requête SQL sur les données chargées. Les données sont disponibles sous le nom `data`.", icon="💡")
+                        init_analysis_state(i, 'query', analysis['params'].get('query', 'SELECT * FROM data LIMIT 10')) # Default query
+                        
+                        query_input = st.text_area("Entrez votre requête SQL:", value=analysis['params']['query'], height=150, key=f"sql_query_input_{analysis_id}")
+                        st.session_state.analyses[i]['params']['query'] = query_input
+
+                        if st.button(f"Exécuter Requête SQL {i+1}", key=f"run_sql_query_{analysis_id}"):
+                            current_params = st.session_state.analyses[i]['params'].copy()
+                            sql_query = current_params.get('query', '').strip()
+
+                            if not sql_query:
+                                st.warning("Veuillez entrer une requête SQL.")
+                            else:
+                                try:
+                                    # Use pandasql to execute the query
+                                    # The dataframe is available as 'data' in the query context
+                                    from pandasql import sqldf
+                                    
+                                    # Ensure the 'data' variable is available in the execution context
+                                    # sqldf requires the dataframe to be in the global or local scope
+                                    # We pass it explicitly via locals()
+                                    result_df = sqldf(sql_query, locals())
+
+                                    if result_df is not None:
+                                        st.session_state.analyses[i]['result'] = result_df
+                                        st.session_state.analyses[i]['executed_params'] = current_params
+                                        st.rerun()
+                                    else:
+                                        st.warning("La requête n'a retourné aucun résultat.")
+
+                                except Exception as e:
+                                    st.error(f"Erreur lors de l'exécution de la requête SQL {i+1}: {e}")
+                                    st.session_state.analyses[i]['result'] = None
+                                    st.session_state.analyses[i]['executed_params'] = current_params # Save params even if failed
+
+                    # --- AFFICHAGE RÉSULTAT ---
+                    result_data = st.session_state.analyses[i].get('result')
+                    executed_params_display = st.session_state.analyses[i].get('executed_params')
+                    if result_data is not None:
+                        st.markdown("---"); st.write(f"**Résultat Analyse {i+1}:**")
+                        if executed_params_display:
+                            params_str_list = []
+                            for k,v in executed_params_display.items():
+                                if v is not None and v != [] and k not in ['type']:
+                                     v_repr = f"[{v[0]}, ..., {v[-1]}] ({len(v)})" if isinstance(v, list) and len(v) > 3 else str(v)
+                                     k_simple = k.replace('_graph','').replace('desc','').replace('_columns','').replace('column','').replace('_',' ').strip().title()
+                                     params_str_list.append(f"{k_simple}={v_repr}")
+                            if params_str_list: st.caption(f"Paramètres: {'; '.join(params_str_list)}")
+                        analysis_type_display = st.session_state.analyses[i]['type'] # Renamed to avoid conflict
+                        try:
+                            if analysis_type_display in ['aggregated_table', 'descriptive_stats', 'sql_query'] and isinstance(result_data, pd.DataFrame):
+                                if analysis_type_display == 'aggregated_table':
+                                    # Apply formatting to aggregated table
+                                    # Identify numerical columns in the aggregated result
+                                    agg_numerical_cols = result_data.select_dtypes(include=np.number).columns.tolist()
+                                    # Exclude group-by columns from formatting if they are numeric (unlikely but safe)
+                                    group_by_cols = st.session_state.analyses[i]['executed_params'].get('group_by_columns', [])
+                                    cols_to_format = [col for col in agg_numerical_cols if col not in group_by_cols]
+                                    
+                                    format_dict = {col: '{:,.2f}' for col in cols_to_format} # Format numerical columns to 2 decimal places with comma separator
+                                    
+                                    # Handle the 'count' column specifically if it exists and is not a group-by column
+                                    if 'count' in result_data.columns and 'count' not in group_by_cols:
+                                         format_dict['count'] = '{:,}' # Format count as integer with comma separator
+
+                                    st.dataframe(result_data.style.format(format_dict), use_container_width=True)
+                                else: # descriptive_stats or sql_query
+                                    st.dataframe(result_data.T if analysis_type_display == 'descriptive_stats' else result_data, use_container_width=True) # Transpose only for descriptive_stats
                             elif analysis_type_display == 'graph' and isinstance(result_data, go.Figure):
                                 st.plotly_chart(result_data, use_container_width=True)
                             else: st.write("Résultat non standard:"); st.write(result_data)