Numpy與list增減元素對比

2022-10-09 11:24:13 字數 2803 閱讀 8678

都知道numpy可以加快python的運算速度，但是並不是所有地方都快，在元素的增刪方面要遠遠慢於list。看以下例子：

例一：

# list新增元素


l = 


start1 = time.time()


print("start:", start1)


for i in range(100000):


end1 = time.time()


print("end", end1)


print("span:", end1 - start1)


# start: 1648979215.742928


# end 1648979215.742928


# span: 0.0
例二：

arr = np.array()

start2 = time.time()

print("start:", start2)

for i in range(100000):

end2 = time.time()

print("end", end2)

print("span:", end2 - start2)

# start: 1648974264.3777995

# end 1648974266.2688227

# span: 1.8910231590270996

例三：

# numpy.hstack()新增元素


arr = np.array()


start2 = time.time()


print("start:", start2)


for i in range(100000):


arr = np.hstack([arr, i])


end2 = time.time()


print("end", end2)


print("span:", end2 - start2)


# start: 1648978917.5062604


# end 1648978919.4940002


# span: 1.9877398014068604
例四：

# list新增行元素


l = 


start1 = time.time()


print("start:", start1)


for i in range(100000):


end1 = time.time()


print("end", end1)


print("span:", end1 - start1)


# start: 1648978962.1275697


# end 1648978962.2210128


# span: 0.09344315528869629
例五：

# numpy.vstack()新增行元素


arr = np.zeros(5)


a = np.array([1, 2, 3 ,4, 5])


start2 = time.time()


print("start:", start2)


for i in range(100000):


arr = np.vstack([arr, a])


end2 = time.time()


print("end", end2)


print("span:", end2 - start2)


# start: 1648979036.896138


# end 1648979083.5973537


# span: 46.701215744018555
例六：

# 使用list新增元素後再轉換成numpy


l = 


start1 = time.time()


print("start:", start1)


for i in range(100000):


arr = np.array(l)


end1 = time.time()


print("end", end1)


print("span:", end1 - start1)


# start: 1648979211.1942384


# end 1648979211.2098572


# span: 0.01561880111694336
例七：

# list新增行元素後再轉換成numpy


l = 


start1 = time.time()


print("start:", start1)


for i in range(100000):


arr = np.array(l)


end1 = time.time()


print("end", end1)


print("span:", end1 - start1)


# start: 1648979279.2713783


# end 1648979279.3811817


# span: 0.10980343818664551
綜上所述，在元素增刪方面，list的效能遠遠好於numpy。但是有些場景確實只能用numpy的，或者用numpy更好的就另說了。

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