type wrong when using sklearn and pandas.Dataframe

Question

I want to use sklearn to do some predict and i stored my data in a Dataframe.

Data = DataFrame(columns = columns,index = range(1,501))

The data has no problem.

from sklearn.cross_validation import train_test_split
Xtrain,Xtest,Ytrain,Ytest = train_test_split(Data[columns[0:5]],Data[columns[5:6]],test_size = 0.25,random_state = 33)

aslo tried:

Xtrain,Xtest,Ytrain,Ytest = train_test_split(np.array(Data[columns[0:5]]),np.array(Data[columns[5:6]]),test_size = 0.25,random_state = 33)
from sklearn.linear_model import LogisticRegression
ss = StandardScaler()
Xtrain = ss.fit_transform(Xtrain)
Xtest = ss.transform(Xtest)
lr = LogisticRegression()
lr.fit(Xtrain,Ytrain)

and the wrong message is:

Traceback (most recent call last): 

    File "/Volumes/sogou_baidu.py", line 148, in <module> 
        lr.fit(Xtrain,Ytrain) 
    File "/Users/liumengyang/anaconda/lib/python3.5/site-packages/skl‌​earn/linear_model/lo‌​gistic.py", line 1143, in 
        fit check_classification_targets(y) 
    File "/Users/liumengyang/anaconda/lib/python3.5/site-packages/skl‌​earn/utils/multiclas‌​s.py", line 173, in 
        check_classification_targets raise ValueError("Unknown label type: %r" % y)

    ValueError: Unknown label type: array([-1, -1, 1, -1, 1, -1, 0, -1, 1, -2, 0, -1, 1, 1, 0, -1, 1, 0, 1, -1, 0, 0, 1, -1, -1, 0, -1, -1, -1, 0, -1, -1, 0, 1, 0, -1, 1], dtype=object)

Under normal circumstances , the parameters of lr.fit() should be two array , but now use the DataFrame as parameter , there is a redundant parameter “dtype=object” , how could i solve this problem ？