比较两个numpy数组并替换on的值

2024-04-28 13:14:17 发布

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我有两个numpy数组,A和B。A包含dtypes=['ID','Value','Type'],B包含dtypes=['ID','Value']。你知道吗

实际上,我想用“B”中的值替换A中的“Value”,但只替换两者中的“ID”(因此B中的ID也在A中)。你知道吗

A = array([[1,2,3,4,5,6,7],[0.785, 0.985, 0.8562, 0.9652, 0.664, 0.962, 0.872],['sio', 'sco', 'sio', 'sco', 'sio', 'sco', 'sio']])
B = array([[1,2,3],[0.85,0.4585,0.8436]])

A和B的长度可能在大小上不同,因此需要映射值,而不是假设id的顺序都相同。你知道吗

最快的方法是什么?你知道吗


Tags: 方法numpyid顺序valuetype数组array
2条回答

希望这对您有所帮助,我使用了OrderedDict以防您的数据不仅仅是按int排序的:

from collections import OrderedDict

A = [[1,2,3,4,5,6,7],[0.785,0.985,0.8562,0.9652,0.664,0.962,0.872],[' sio', 'sco', 'sio', 'sco', 'sio', 'sco','sio']]
B = [[1,2,3],[0.85,0.4585,0.8436]]

a = OrderedDict(zip(*A[:2]))
b = dict(zip(*B))

c = OrderedDict([(k, b[k] if k in b else v) for k, v in a.items()])

A = [c.keys(), c.values(), A[2]]

输出:

[[1, 2, 3, 4, 5, 6, 7],
 [0.85, 0.4585, 0.8436, 0.9652, 0.664, 0.962, 0.872],
 [' sio', 'sco', 'sio', 'sco', 'sio', 'sco', 'sio']]

这对你来说够快吗?你知道吗

import numpy

A = numpy.array([[1,2,3,4,5,6,7],[0.785,0.985,0.8562,0.9652,0.664,0.962,0.872],[' sio', 'sco', 'sio', 'sco', 'sio', 'sco','sio']])
B = numpy.array([[1,2,3],[0.85,0.4585,0.8436]])
for i, x in enumerate(A[0]):
    if x in str(B[0]):
        A[1,i] = B[1,i]
print A

输出:

[['1' '2' '3' '4' '5' '6' '7']
 ['0.85' '0.4585' '0.8436' '0.9652' '0.664' '0.962' '0.872']
 [' sio' 'sco' 'sio' 'sco' 'sio' 'sco' 'sio']]

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