Question

我已经搜索了将.csv行转换为向量的代码，以使用Tensorflow的DL项目中的数据集。我找到了以下代码：

import numpy as np
def extract_data(filename):
    #arrays to hold the labels and features vectors
   labels = []
   fvecs= []

    #iterate over the rows,spplit the label from the features
    #convert labels to integers and features to floats
    for line in file(filename):
       row = line.split(',')
       labels.append(int(row[0]))
       fvecs.append([float(x) for x in row[1:2]])
   #convert the array of float arrays into a numpy float matrix
   fvecs_np = np.matrix(fvecs).astype(np.float33)
   #convert the array of int labels into numpy array
   labels_np = np.array(labels).astype(dtype=np.uint8)
   #convert the int numpy array into a one_hot matrix
   label_onehot = (np.arrange(NUM_LABELS) == labels_np[:,None])).astype(np.float32)
   #return a pair of the features matrix and the one_hot label matrix
   return fvecs_np, label_onehot

我试图遍历代码并学习它。然后，我遇到了这一行：

fvecs.append([float(x) for x in row[1:2]])

似乎可以获取每行的第二个和第三个索引的值并将其提供给x，但我无法完全理解他为什么在float(x)之前使用for以及为什么将{ {1}}放在方括号中，然后将其附加到for

Answer 1

也许这可以帮助您理解：

# create a list of ints
x = [-2, -1, 0, 1, 2]
print('x: ', x)

# create an identical list to x
y = [element for element in x]
print('y: ', y)

# create a list where each element is the square of the elment in x
s = [element**2 for element in x]
print('s: ', s)

# append a list to a list (to make a list of lists)
d = []
d.append(x)
d.append(s)
print('d: ', d)

# doing it all together
d = []
d.append([-2, -1, 0, 1, 1]) # the same as d.append(x)
d.append([element**2 for element in x]) # the same as d.append(s)
print('d_again: ', d)

输出：

('x: ', [-2, -1, 0, 1, 2])
('y: ', [-2, -1, 0, 1, 2])
('s: ', [4, 1, 0, 1, 4])
('d: ', [[-2, -1, 0, 1, 2], [4, 1, 0, 1, 4]])
('d_again: ', [[-2, -1, 0, 1, 1], [4, 1, 0, 1, 4]])

列表理解的使用被认为是“ pythonic”

这个“ for”结构如何在python中工作

1 个答案: