使用numpy在第一矩阵列中搜索数组，并获取下一列的值

Question

Having the following arrays (I understand the first one is call a matrix)

ids = np.array([['Peter Parker','Spiderman'],['Ben Reilly','Scarlet Spider'],['Norman Osborn','Green Goblin'],['Bruce Banner','Hulk']])

And

heroes=np.array(['Spiderman','Scarlet Spider','Capitan America','Iron Man'])

I'm able to find the "heroes" values that matches rows in "ids" but I can only print the matches like

 print(ids[np.where(ids==(np.row_stack(heroes)))])

Which outputs

['Spiderman' 'Scarlet Spider']

Is it (and how) possible to print them like ?

['Peter Parker' 'Ben Reilly']

note This is a given exercise, I don't expect other requirements like having the qty of elements on the heroes array diff from the # of rows in the ids array (this would it break my current code due the use of row_stack ).

But I noticed that my where would not find duplicated values on the ids array (like if I have 2 "Spiderman" with diff name and both names appears in the heroes array), feel free to extend to this but main question is what I just wrote with no other given restrictions.

Answer 1

You can use np.argwhere and indexing to get the names. The inner [:,0] gives you the two subarrays containing the names and the outer [:,0] gives you the first element (name) from each of the subarrays.

ids[np.argwhere(ids==(np.row_stack(heroes)))[:,0]][:, 0]
# array(['Peter Parker', 'Ben Reilly'])