from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler, LabelEncoder

def divSet(data, labels = None, test_size=0.2, random_state=None):

  encoder = LabelEncoder()

  # 最后一列是标签
  X = data.iloc[:, :-1]
  y = data.iloc[:, -1]
  
  if labels:
    labels = encoder.fit_transform(labels)
  else:
    encoder.fit(y)
  
  # 分割数据集为训练集和测试集
  X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, random_state=random_state)
  # 标准化特征
  scaler = StandardScaler()
  X_train = scaler.fit_transform(X_train)
  X_test = scaler.transform(X_test)
  
  # 编码标签
  y_train = encoder.transform(y_train.values.reshape(-1, 1))
  y_test = encoder.transform(y_test.values.reshape(-1, 1))
  
  return X_train, X_test, y_train, y_test, encoder