Create utils/preprocessing.py

utils/preprocessing.py

@@ -0,0 +1,11 @@
+# utils/preprocessing.py
+import pandas as pd
+from sklearn.preprocessing import StandardScaler
+
+def preprocess_data_for_streamlit(data_path):
+    df = pd.read_csv(data_path)
+    df = feature_engineering(df)  # Assuming feature_engineering is defined
+    X = df.drop('label', axis=1)
+    scaler = StandardScaler()
+    X_scaled = scaler.fit_transform(X)
+    return df, X_scaled