如何删除"；0“；来自列车数据的值。python

我正在使用python使用fashion mnist数据集进行分类。我想要构建的分类器是NaiveBayes，当运行我构建的代码时，我下载的数据似乎有零值，在一些数学计算中，变量被这些零值除以，我不希望发生这种情况。所以我需要一种方法从我想要分类的数据中“删除”这些零值。数据外观的示例如下：

[[0.         0.         0.         ... 0.         0.         0.        ]
 [0.         0.         0.         ... 0.         0.         0.        ]
 [0.         0.         0.         ... 0.         0.         0.        ]
 ...
 [0.         0.         0.         ... 0.27450982 0.         0.        ]
 [0.         0.         0.         ... 0.         0.         0.        ]
 [0.         0.         0.         ... 0.         0.         0.        ]]

该示例仅包含10行60000个数据

我正在尝试使用以下命令删除零：

Xtrain,ytrain),(Xtest,ytest) = fashion_mnist.load_data() # loading data

Xtrain = Xtrain.astype('float32') # I want from this to delete zero values 
Xtest = Xtest.astype('float32')   # and from that
Xtrain=Xtrain/255.0
Xtest=Xtest/255.0


    #Reshaping data 
Xtest=Xtest.reshape(Xtest.shape[0], Xtest.shape[1] * Xtest.shape[2])
Xtrain =Xtrain.reshape(Xtrain.shape[0], Xtrain.shape[1] * Xtrain.shape[2])

naive_bayes = NaiveBayes()
# So before i send this datas to fit function in order to run the classification i am trying 
# with not working way to delete thouse values 
Xtrain_non_zero = []
for i in range(len(Xtrain)):
    for j in range(len(Xtrain)):
        if Xtrain[i][j]!=0:
            Xtrain_non_zero.append(Xtrain[i][j])
print(Xtrain_non_zero)

---

除非我误解了你是不是在寻找

Xtrain\u non\u zero=Xtrain[Xtrain！=0]

？@jwalton你好，谢谢你的回复，当我这么做的时候，我得到的是一个满是假的数组