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With a small 10 line test file I tried 2 approaches - parse the whole thing and select the last N lines, versus load all lines, but only parse the last N:
使用一個小的10行測試文件，我嘗試了2種方法 - 解析整個事物並選擇最后N行，而不是加載所有行，但只解析最后N：
In [1025]: timeit np.genfromtxt(stack38704949.txt,delimiter=,)[-5:]
1000 loops, best of 3: 741 µs per loop
In [1026]: %%timeit
...: with open(stack38704949.txt, b) as f:
...: lines = f.readlines()
...: np.genfromtxt(lines[-5:],delimiter=,)
1000 loops, best of 3: 378 µs per loop
This was tagged as a duplicate of Efficiently Read last rows of CSV into DataFrame. The accepted answer there used
這被標記為有效地將最后 行CSV讀入DataFrame的副本。那里接受的答案
from collections import deque
and collected the last N lines in that structure. It also u
