process_cinetic_shift_features.py

for feature in ["x1","x2","x3"]:
  
  # We create a shifted feature matching the original one
  feature_new_name = feature + "_shifted"
  
  # The shift is determined randomly
  random_shift = np.random.randint(10,50)
  
  df[feature_new_name] = df[feature].shift(-random_shift)
  
  print(feature, "shifted of", -random_shift)
df = df.dropna()