Update app.py

app.py

@@ -123,16 +123,24 @@ def generar_mapa_calor(df):
 # Gráfico univariado
 def grafico_univariado(var, genero, localidades, compromiso_renal, antecedentes):
     df = aplicar_filtros(data, genero, localidades, compromiso_renal, antecedentes)
-    if df.empty:
+    if df.empty or var not in df.columns:
         return None
+
     plt.figure(figsize=(6, 4))
-    if df[var].dtype == 'object':
-        sns.countplot(data=df, x=var)
+    ax = None
+    if pd.api.types.is_numeric_dtype(df[var]):
+        ax = sns.histplot(df[var].dropna(), kde=True)
     else:
-        sns.histplot(df[var], kde=True)
+        orden = df[var].value_counts().index
+        ax = sns.countplot(data=df, x=var, order=orden)
+        for container in ax.containers:
+            ax.bar_label(container, fontsize=9, label_type='edge')
+
+        plt.xticks(rotation=30)
+
     plt.title(f"Distribución de {var}")
-    path = f"uni_{var}.png"
     plt.tight_layout()
+    path = f"uni_{var}.png"
     plt.savefig(path)
     plt.close()
     return path
@@ -142,19 +150,24 @@ def grafico_bivariado(x, y, genero, localidades, compromiso_renal, antecedentes)
     df = aplicar_filtros(data, genero, localidades, compromiso_renal, antecedentes)
     if df.empty or x not in df.columns or y not in df.columns:
         return None
+
     plt.figure(figsize=(6, 4))
+    ax = None
     if pd.api.types.is_numeric_dtype(df[x]) and pd.api.types.is_numeric_dtype(df[y]):
-        sns.scatterplot(data=df, x=x, y=y)
+        ax = sns.scatterplot(data=df, x=x, y=y)
     elif pd.api.types.is_numeric_dtype(df[x]) and not pd.api.types.is_numeric_dtype(df[y]):
-        sns.boxplot(data=df, x=y, y=x)
+        ax = sns.boxplot(data=df, x=y, y=x)
         plt.xticks(rotation=30)
     elif pd.api.types.is_numeric_dtype(df[y]) and not pd.api.types.is_numeric_dtype(df[x]):
-        sns.boxplot(data=df, x=x, y=y)
+        ax = sns.boxplot(data=df, x=x, y=y)
         plt.xticks(rotation=30)
     else:
         orden_x = df[x].value_counts().index
-        sns.countplot(data=df, x=x, hue=y, order=orden_x)
+        ax = sns.countplot(data=df, x=x, hue=y, order=orden_x)
+        for container in ax.containers:
+            ax.bar_label(container, fontsize=8, label_type='edge')
         plt.xticks(rotation=30)
+
     plt.title(f"{x} vs {y}")
     plt.tight_layout()
     path = f"bi_{x}_{y}.png"