Update app.py

app.py

@@ -27,12 +27,20 @@ agent = CodeAgent(
     )
 
 # Data cleaning function
+from sklearn.preprocessing import LabelEncoder
+
 def clean_data(df):
     df = df.dropna(how='all', axis=1).dropna(how='all', axis=0)
+
+    # Encode categorical features
+    for col in df.select_dtypes(include='object').columns:
+        df[col] = df[col].astype(str)
+        df[col] = LabelEncoder().fit_transform(df[col])
+
     df = df.fillna(df.mean(numeric_only=True))
-    df = df.select_dtypes(include=[np.number])
     return df
 
+
 # Global dataframe
 df_global = None