根据来自另一个数组的数据对一个numpy数组进行排序

我有两组数组data和result. result在data中包含相同的元素，但具有额外的列且未排序.我想重新排列result数组，使其与data中的行相同，同时在进行排序时将关联的值与该行的其余部分一起放入最后一列.

I have two sets of array data and result. result contains the same elements in data but with an extra column and in unsorted order. I want to rearrange the result array so that it is in the same order as the rows in data , while bringing the associated value into the last column with the rest of the row when doing the sorting.

data = np.array([[0,1,0,0],[1,0,0,0],[0,1,1,0],[0,1,0,1]])
result = np.array([[0,1,1,0,1],[1,0,0,0,0],[0,1,0,0,1],[0,1,0,1,0]])

# this is what the final sorted array should look like:
'''
array([[0, 1, 0, 0, 1],
       [1, 0, 0, 0, 0],
       [0, 1, 1, 0, 1],
       [0, 1, 0, 1, 0]])
 '''

我尝试执行argsort以便将data反转为排序顺序，然后将其应用于result，但是argsort似乎是根据每个元素对数组的顺序进行排序，而我想要排序以将data[:,4]的每一行视为一个整体.

I've tried doing argsort in order to reverse data into the sorted order then applying that to result but argsort seems to sort the order of the array based on each element, whereas I want the sort to treat each row of the data[:,4] as a whole.

ind = np.argsort(data)
indind =np.argsort(ind)
ind
array([[0, 2, 3, 1],
   [1, 2, 3, 0],
   [0, 3, 1, 2],
   [0, 2, 1, 3]])

执行这种按行排序的好方法是什么?

What is a good way to do this kind of sorting by rows?