Question

例如我有一个清单清单

[[1,2,3], [4,5,6], [7,8,9], [10,11,12], ...]

我想在for循环中添加所有列表并创建一个ndarray，

喜欢跟随

for list in lists:
    sum function...

结果就是我想要的

[22, 26, 30]

我如何用漂亮的代码编写它？

Answer 1

如果您使用的是NumPy，则非常简单：

\p{Lu}

对于纯Python解决方案：

(?=...

NumPy解决方案将更快。

import numpy as np

l = [[1,2,3], [4,5,6], [7,8,9], [10,11,12]]
arr = np.array(l)
result = arr.sum(axis=0)
print(result)
# [22 26 30]

Answer 2

您只需使用python的基本知识就可以做到这一点而无需Numpy。（所有子列表的长度必须相同）

l =  [[1,2,3], [4,5,6], [7,8,9], [10,11,12]]
result = [sum(subL[i] for subL in l) for i in range(len(l[0]))]

或者，没有列表理解：

result = []
for i in range(len(l[0])):
    n = 0
    for x in l:
        n += subL[i]
    result.append(n)

两者都产生输出[22, 26, 30]。

如果您对性能感兴趣，我会写这个（不确定它是否正确）：

from timeit import timeit
import numpy as np

l = [[1,2,3], [4,5,6], [7,8,9], [10,11,12]]

def listComprehension():
    result = [sum(subL[i] for subL in l) for i in range(len(l[0]))]

def basic():
    result = []
    for i in range(len(l[0])):
        n = 0
        for subL in l:
            n += subL[i]
        result.append(n)

def zipped():
    result = [sum(column) for column in zip(*l)]

def numpyied():
    arr = np.array(l)
    result = arr.sum(axis=0)

print(timeit("listComprehension()", setup = "from __main__ import listComprehension"))
# 3.738487364
print(timeit("basic()", setup = "from __main__ import basic"))
# 1.953782115
print(timeit("zipped()", setup = "from __main__ import zipped"))
# 1.413262091
print(timeit("numpyied()", setup = "from __main__ import numpyied"))
# 9.576366059999998

令人惊讶的是numpy慢一些，但我不能说为什么。（后两个功能取自@Tomothy32's answer）

我想在for循环中添加所有列表并制作一个ndarray

2 个答案: