Update src/module/Data_Exploration.py

src/module/Data_Exploration.py

@@ -97,50 +97,50 @@ class AdvancedAnalyzer:  # <--- RENOMMAGE ICI
 
     
     def plot_numeric_summary(self, table_keyword, top_n=8):
-    df = self.get_df(table_keyword)
-    if df is None: return
-    num_cols = df.select_dtypes(include='number').columns.tolist()
-    if not num_cols:
-        st.info("Aucune colonne numérique.")
-        return
-    num_cols = num_cols[:top_n]
-    for col in num_cols:
-        c1, c2 = st.columns([2,1])
-        with c1:
-            fig = px.histogram(df, x=col, nbins=60, marginal='box', title=f"Distribution : {col}")
-            st.plotly_chart(fig, use_container_width=True)
-        with c2:
-            st.write(df[col].describe().to_frame().T)
+        df = self.get_df(table_keyword)
+        if df is None: return
+        num_cols = df.select_dtypes(include='number').columns.tolist()
+        if not num_cols:
+            st.info("Aucune colonne numérique.")
+            return
+        num_cols = num_cols[:top_n]
+        for col in num_cols:
+            c1, c2 = st.columns([2,1])
+            with c1:
+                fig = px.histogram(df, x=col, nbins=60, marginal='box', title=f"Distribution : {col}")
+                st.plotly_chart(fig, use_container_width=True)
+            with c2:
+                st.write(df[col].describe().to_frame().T)
 
 
     #----Corrélation (heatmap) pour numériques
     
     def plot_correlation(self, table_keyword):
-    df = self.get_df(table_keyword)
-    if df is None: return
-    num = df.select_dtypes(include='number').dropna(axis=1, how='all')
-    if num.shape[1] < 2:
-        st.info("Pas assez de colonnes numériques pour corrélation.")
-        return
-    corr = num.corr()
-    fig = px.imshow(corr, text_auto=".2f", title=f"Heatmap corrélations ({table_keyword})")
-    st.plotly_chart(fig, use_container_width=True)
+        df = self.get_df(table_keyword)
+        if df is None: return
+        num = df.select_dtypes(include='number').dropna(axis=1, how='all')
+        if num.shape[1] < 2:
+            st.info("Pas assez de colonnes numériques pour corrélation.")
+            return
+        corr = num.corr()
+        fig = px.imshow(corr, text_auto=".2f", title=f"Heatmap corrélations ({table_keyword})")
+        st.plotly_chart(fig, use_container_width=True)
 
     # ----- Vérification d'intégrité référentielle (join rates)
     
     def referential_check(self, left_table, right_table, key='patient_id'):
-    left = self.get_df(left_table); right = self.get_df(right_table)
-    if left is None or right is None:
-        st.warning("Tables introuvables pour check référentiel.")
-        return
-    left_keys = set(left[key].dropna().unique())
-    right_keys = set(right[key].dropna().unique())
-    in_left_not_right = len(left_keys - right_keys)
-    in_right_not_left = len(right_keys - left_keys)
-    st.write(f"- Clés {key} dans {left_table}: {len(left_keys):,}")
-    st.write(f"- Clés {key} dans {right_table}: {len(right_keys):,}")
-    st.metric("Dans left mais pas right", f"{in_left_not_right:,}")
-    st.metric("Dans right mais pas left", f"{in_right_not_left:,}")
+        left = self.get_df(left_table); right = self.get_df(right_table)
+        if left is None or right is None:
+            st.warning("Tables introuvables pour check référentiel.")
+            return
+        left_keys = set(left[key].dropna().unique())
+        right_keys = set(right[key].dropna().unique())
+        in_left_not_right = len(left_keys - right_keys)
+        in_right_not_left = len(right_keys - left_keys)
+        st.write(f"- Clés {key} dans {left_table}: {len(left_keys):,}")
+        st.write(f"- Clés {key} dans {right_table}: {len(right_keys):,}")
+        st.metric("Dans left mais pas right", f"{in_left_not_right:,}")
+        st.metric("Dans right mais pas left", f"{in_right_not_left:,}")
 
 
     # --- VUES ANALYTIQUES AVANCÉES ---