我有以下 numpy 數組（自 1957 年以來該國的火箭發射次數），我想按發射次數的升序對其進行排序。 ['Australia', 6.0], ['Brazil', 3.0], ['China', 269.0], ['France', 303.0], ['India', 76.0], ['Iran', 14.0], ['Israel', 11.0], ['Japan', 126.0], ['Kazakhstan', 701.0], ['Kenya', 9.0], ['New Zealand', 13.0], ['North Korea', 5.0], ['Pacific Ocean', 36.0], ['Russian Federation', 1398.0], ['South Korea', 3.0], ['USA', 1351.0]問題是， np.sort(a, axis = 0) 只對值進行排序，但國家之間沒有聯系，因此 ei 朝鮮發射了 269 枚火箭（可能比 5 枚更有可能）或者，如果我執行 np.sort(a, axis = 1) 那么我會收到一條錯誤消息類型錯誤：“float”和“str”實例之間不支持“<”任何想法將不勝感激！
2 回答
拉風的咖菲貓
TA貢獻1995條經驗 獲得超2個贊
import numpy as np
data = [
['Australia', 6.0],
['Brazil', 3.0],
['China', 269.0],
['France', 303.0],
['India', 76.0],
['Iran', 14.0],
['Israel', 11.0],
['Japan', 126.0],
['Kazakhstan', 701.0],
['Kenya', 9.0],
['New Zealand', 13.0],
['North Korea', 5.0],
['Pacific Ocean', 36.0],
['Russian Federation', 1398.0],
['South Korea', 3.0],
['USA', 1351.0]
]
我們可以創建一個結構化數組，然后按鍵對其進行排序：
dtype = [
('name', '<U18'),
('rockets', float)
]
data = np.array([tuple(x) for x in data], dtype=dtype)
sorted_data = np.sort(data, order=['rockets'])
print(sorted_data)
侃侃爾雅
TA貢獻1801條經驗 獲得超16個贊
使用 python 列表排序很容易：
In [208]: alist = [ ['Australia', 6.0],
...: ['Brazil', 3.0],
...: ['China', 269.0],
...: ['France', 303.0],
...: ['India', 76.0],
...: ['Iran', 14.0],
...: ['Israel', 11.0],
...: ['Japan', 126.0],
...: ['Kazakhstan', 701.0],
...: ['Kenya', 9.0],
...: ['New Zealand', 13.0],
...: ['North Korea', 5.0],
...: ['Pacific Ocean', 36.0],
...: ['Russian Federation', 1398.0],
...: ['South Korea', 3.0],
...: ['USA', 1351.0]]
In [209]: newlist = sorted(alist, key=lambda x: x[1])
In [210]: newlist
Out[210]:
[['Brazil', 3.0],
['South Korea', 3.0],
['North Korea', 5.0],
['Australia', 6.0],
['Kenya', 9.0],
['Israel', 11.0],
['New Zealand', 13.0],
['Iran', 14.0],
['Pacific Ocean', 36.0],
['India', 76.0],
['Japan', 126.0],
['China', 269.0],
['France', 303.0],
['Kazakhstan', 701.0],
['USA', 1351.0],
['Russian Federation', 1398.0]]
使用對象 dtype 數組（保留字符串和浮點列）：
In [211]: arr = np.array(alist, object)
In [212]: arr
Out[212]:
array([['Australia', 6.0],
['Brazil', 3.0],
['China', 269.0],
['France', 303.0],
...
['USA', 1351.0]], dtype=object)
只需查看第二列即可獲取排序索引：
In [213]: idx = np.argsort(arr[:,1])
In [214]: idx
Out[214]: array([ 1, 14, 11, 0, 9, 6, 10, 5, 12, 4, 7, 2, 3, 8, 15, 13])
In [215]: arr[idx]
Out[215]:
array([['Brazil', 3.0],
['South Korea', 3.0],
['North Korea', 5.0],
['Australia', 6.0],
['Kenya', 9.0],
...
['Russian Federation', 1398.0]], dtype=object)
其他答案中的結構化數組方法也很好。
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