获得ValueError:endog和exog的索引不对齐

Question

当我使用FOR循环运行迭代来构建多个模型时,我遇到了上述错误.前两个具有相似数据集的模型构建良好.在构建第三个模型时,我收到此错误.抛出错误的代码是当我使用python的Statsmodel包调用sm.logit()时:

y = y_mort.convert_objects(convert_numeric=True)

#Building Logistic model_LSVC
print("Shape of y:", y.shape, " &&Shape of X_selected_lsvc:", X.shape)
print("y values:",y.head())
logit = sm.Logit(y,X,missing='drop') 

出现的错误:

Shape of y: (9018,)  &&Shape of X_selected_lsvc: (9018, 59)
y values: 0    0
1    1
2    0
3    0
4    0
Name: mort, dtype: int64
ValueError                                Traceback (most recent call last)
<ipython-input-8-fec746e2ee99> in <module>()
    160     print("Shape of y:", y.shape, " &&Shape of X_selected_lsvc:", X.shape)
    161     print("y values:",y.head())
--> 162     logit = sm.Logit(y,X,missing='drop')
    163     # fit the model
    164     est = logit.fit(method='cg')

D:\Anaconda3\lib\site-packages\statsmodels\discrete\discrete_model.py in __init__(self, endog, exog, **kwargs)
    399 
    400     def __init__(self, endog, exog, **kwargs):
--> 401         super(BinaryModel, self).__init__(endog, exog, **kwargs)
    402         if (self.__class__.__name__ != 'MNLogit' and
    403                 not np.all((self.endog >= 0) & (self.endog <= 1))):

D:\Anaconda3\lib\site-packages\statsmodels\discrete\discrete_model.py in __init__(self, endog, exog, **kwargs)
    152     """
    153     def __init__(self, endog, exog, **kwargs):
--> 154         super(DiscreteModel, self).__init__(endog, exog, **kwargs)
    155         self.raise_on_perfect_prediction = True
    156 

D:\Anaconda3\lib\site-packages\statsmodels\base\model.py in __init__(self, endog, exog, **kwargs)
    184 
    185     def __init__(self, endog, exog=None, **kwargs):
--> 186         super(LikelihoodModel, self).__init__(endog, exog, **kwargs)
    187         self.initialize()
    188 

D:\Anaconda3\lib\site-packages\statsmodels\base\model.py in __init__(self, endog, exog, **kwargs)
     58         hasconst = kwargs.pop('hasconst', None)
     59         self.data = self._handle_data(endog, exog, missing, hasconst,
---> 60                                       **kwargs)
     61         self.k_constant = self.data.k_constant
     62         self.exog = self.data.exog

D:\Anaconda3\lib\site-packages\statsmodels\base\model.py in _handle_data(self, endog, exog, missing, hasconst, **kwargs)
     82 
     83     def _handle_data(self, endog, exog, missing, hasconst, **kwargs):
---> 84         data = handle_data(endog, exog, missing, hasconst, **kwargs)
     85         # kwargs arrays could have changed, easier to just attach here
     86         for key in kwargs:

D:\Anaconda3\lib\site-packages\statsmodels\base\data.py in handle_data(endog, exog, missing, hasconst, **kwargs)
    564     klass = handle_data_class_factory(endog, exog)
    565     return klass(endog, exog=exog, missing=missing, hasconst=hasconst,
--> 566                  **kwargs)

D:\Anaconda3\lib\site-packages\statsmodels\base\data.py in __init__(self, endog, exog, missing, hasconst, **kwargs)
     74         # this has side-effects, attaches k_constant and const_idx
     75         self._handle_constant(hasconst)
---> 76         self._check_integrity()
     77         self._cache = resettable_cache()
     78 

D:\Anaconda3\lib\site-packages\statsmodels\base\data.py in _check_integrity(self)
    450                 (hasattr(endog, 'index') and hasattr(exog, 'index')) and
    451                 not self.orig_endog.index.equals(self.orig_exog.index)):
--> 452             raise ValueError("The indices for endog and exog are not aligned")
    453         super(PandasData, self)._check_integrity()
    454 

ValueError: The indices for endog and exog are not aligned

y矩阵和X矩阵具有(9018,),(9018,59)的形状.因此,不会出现依赖变量和自变量的任何不匹配.任何的想法？

Answer 1

尝试将y转换为sm.Logit()行之前的列表.

y = list(y)

Answer 2

Nan您检查过您的数据中是否有吗？您可以使用np.isNan(X)和np.isNan(y)。我看到您打开了该选项drop，所以我怀疑您的数据中是否包含该选项Nan，那么这将改变您输入的形状。