问题描述
我正在尝试将手写字符数据集重塑为 3D 形式，以便它可以与数字识别数据集连接.我尝试了很多次，但我无法弄清楚如何做到这一点.
I am trying to reshape a handwritten character dataset into 3D form so that it can be concatenated with digit recognition dataset. I tried multiple times, but I couldnt figure out how it can be done.
实际数字识别数据集的形状为 (60000, 28, 28)字符识别数据集的形状为 (372450, 785)，第一列是目标变量.由于排除第一列 28*28=784，因此有可能将其转换为与数字数据集相同的 3D.请就如何做到这一点提出建议?
The actual digit recognition dataset has the shape (60000, 28, 28)The character recognition dataset has the shape (372450, 785) and the first column is target variable. Since excluding first column 28*28=784 there is a possibility that it can be converted to 3D same as digit dataset. Please advice on how this can be done?
对于整个数据框，我需要像 (372450,28,28) 这样的形状
I need a shape like (372450,28,28) for the entire dataframe
提前致谢
推荐答案
形状数组 (372450, 785) 不能被做成 (372450,28,28) 因为 28*28 是 784 而不是 785.但是如果你的意思是将 (372450, 784) 变成 (372450,28,28)，你可以这样做
An array of shape (372450, 785) cannot be made into (372450,28,28) because 28*28 is 784 not 785. But if you meant making a (372450, 784) into (372450,28,28), you could do
arr = df.column_name.values
将从数据框 df 的 column_name 字段中给出一个 numpy 值数组.
will give a numpy array of values from the column_name field of the data frame df.
现在你可以像使用 reshape() 一样
Now you can use reshape() like
arr = arr.reshape(-1,28,28)
现在 arr 将是形状 (372450,28,28).
Now arr will be of shape (372450,28,28).
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