python-3.x - 使用熊猫数据框时出现 KeyError

问题描述

我正在尝试使用 python 实现自定义性能指标。目标是计算给出度量 A 的最低值的最佳概率阈值。我编写了以下代码来计算混淆矩阵和阈值。

def confusion_matrix(self):
        """This method returns the confusion matrix for the given pair of Y and Y_Predicted"""
        
        #y,ypred
        y = self.df["y"]
        ypred = self.df["ypred"]
        self.setVariables()        
        try:
            assert len(y) == len(ypred)
            for val in range(len(df["proba"])):
                print(val)
                if y[val] == 1 and ypred[val] == 1:
                    self._truePositive +=1
                if y[val] == 1 and ypred[val] == 0:
                    self._trueNegative +=1
                if y[val] == 0 and ypred[val] == 1:
                    self._falsePositive +=1
                if y[val] == 0 and ypred[val] == 0:
                    self._falseNegtive +=1
            for i in self._truePositive,self._trueNegative,self._falsePositive,self._falseNegtive:
                self._cnf_matrix.append(i)
            cnfMatrix = self._cnf_matrix.copy()
                
            return np.array(cnfMatrix).reshape(2,2)
  
        except AssertionError:
            print("Input Error: Length of y and ypred is not same.")
      
    
def metricForLowestValues(self):
        """Compute the best threshold of probability which gives lowest values of metric A"""

        dict_metricA = {}

        for item in tqdm(self.df['proba']):
            if item != None:
                self.predict(item)
                cnf = self.confusion_matrix()
                # A=500×number of false negative+100×numebr of false positive
                metricA = 500 * self._falseNegtive + 100* self._falsePositive
                dict_metricA[item] = metricA
                self.df.drop(columns=["ypred"],inplace=True)
            sorted_metricAList = sorted(dict_metricA.items(),key=lambda item:item[1])
            minKey = sorted_metricAList[0][0]
            minValue = dict_metricA[minKey]

        return minKey, minValue

但是当我尝试运行这段代码时，它在计算混淆矩阵时给了我下面的 KeyError 错误。

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-164-38aae4fab9c1> in <module>
----> 1 performance3.metricForLowestValues()

<ipython-input-148-fe3aeec53878> in metricForLowestValues(self)
     91             if item != None:
     92                 self.predict(item)
---> 93                 cnf = self.confusion_matrix()
     94                 # A=500×number of false negative+100×numebr of false positive
     95                 metricA = 500 * self._falseNegtive + 100* self._falsePositive

<ipython-input-148-fe3aeec53878> in confusion_matrix(self)
     30             for val in range(len(df["proba"])):
     31                 print(val)
---> 32                 if y[val] == 1 and ypred[val] == 1:
     33                     self._truePositive +=1
     34                 if y[val] == 1 and ypred[val] == 0:

~/Anaconda/anaconda3/lib/python3.8/site-packages/pandas/core/series.py in __getitem__(self, key)
    869         key = com.apply_if_callable(key, self)
    870         try:
--> 871             result = self.index.get_value(self, key)
    872 
    873             if not is_scalar(result):

~/Anaconda/anaconda3/lib/python3.8/site-packages/pandas/core/indexes/base.py in get_value(self, series, key)
   4403         k = self._convert_scalar_indexer(k, kind="getitem")
   4404         try:
-> 4405             return self._engine.get_value(s, k, tz=getattr(series.dtype, "tz", None))
   4406         except KeyError as e1:
   4407             if len(self) > 0 and (self.holds_integer() or self.is_boolean()):

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_value()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_value()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()

KeyError: 2852

我使用的数据集是 (2852, 2) 形状的。理想情况下，迭代应该发生在 0 到 2851 之间，因为总行数是 2852。我相信这个错误的发生可能是由于生成了额外的行，但我不确定如何修复它。我尝试过滤掉 metricForLowestValues 函数中的 None 值，但不是运气。

我在做吗。有事吗？将不胜感激任何见解。

标签： python-3.xpandasdataframemachine-learningdata-science

python-3.x - 使用熊猫数据框时出现 KeyError

问题描述

解决方案

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