ValueError: Input contains NaN, infinity or a value too large for dtype(‘float64‘)

╰半夏微凉° 2022-11-07 04:23 275阅读 0赞

## 问题 ##

刚开始学习 sklearn ，运行下面的代码时报错，

from sklearn.feature_extraction import DictVectorizer
    from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer
    from  sklearn.preprocessing import  MinMaxScaler,StandardScaler ,Normalizer
    from sklearn.impute import SimpleImputer
    import  numpy as np
    
    import jieba
    
    def im():
        """ 缺失值处理 :return: """
        im  = SimpleImputer(missing_values='NaN',strategy='mean')
        data = im.fit_transform([[1,2],[np.nan,3],[7,6]])
        print(data)
    
    if __name__ == "__main__":   
        im()

运行报错，

ValueError: Input contains NaN, infinity or a value too large for dtype(‘float64’)。具体如下：

Traceback (most recent call last):
      File "E:/pycharm_workspace/matplotlibDemo/feature.py", line 104, in <module>
        im()
      File "E:/pycharm_workspace/matplotlibDemo/feature.py", line 95, in im
        data = im.fit_transform([[1,2],[np.nan,3],[7,6]])
      File "D:\skl3\lib\site-packages\sklearn\base.py", line 699, in fit_transform
        return self.fit(X, **fit_params).transform(X)
      File "D:\skl3\lib\site-packages\sklearn\impute\_base.py", line 288, in fit
        X = self._validate_input(X, in_fit=True)
      File "D:\skl3\lib\site-packages\sklearn\impute\_base.py", line 262, in _validate_input
        raise ve
      File "D:\skl3\lib\site-packages\sklearn\impute\_base.py", line 255, in _validate_input
        copy=self.copy)
      File "D:\skl3\lib\site-packages\sklearn\base.py", line 421, in _validate_data
        X = check_array(X, **check_params)
      File "D:\skl3\lib\site-packages\sklearn\utils\validation.py", line 63, in inner_f
        return f(*args, **kwargs)
      File "D:\skl3\lib\site-packages\sklearn\utils\validation.py", line 664, in check_array
        allow_nan=force_all_finite == 'allow-nan')
      File "D:\skl3\lib\site-packages\sklearn\utils\validation.py", line 106, in _assert_all_finite
        msg_dtype if msg_dtype is not None else X.dtype)
        
    ValueError: Input contains NaN, infinity or a value too large for dtype('float64').

`Input contains NaN, infinity or a value too large for dtype('float64')` 表示 Input 的值包含太长了。

## 解决方法 ##

from sklearn.feature_extraction import DictVectorizer
    from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer
    from  sklearn.preprocessing import  MinMaxScaler,StandardScaler ,Normalizer
    from sklearn.impute import SimpleImputer
    import  numpy as np
    
    import jieba
    
    def im():
        """ 缺失值处理 :return: """
        im  = SimpleImputer(missing_values=np.nan,strategy='most_frequent')
        data = im.fit_transform([[1,2],[np.nan,3],[7,6]])
        print(data)
    
    if __name__ == "__main__":   
        im()

运行结果报错：

[[1. 2.]
     [1. 3.]
     [7. 6.]]