如何用另一个数组中唯一值的索引替换numpy数组中的重复值？

Question

I have an array a with recurring elements, and a second array, b, containing the sorted, unique values from a (as well as an auxilliary "index array", c):

a = np.array(['Bob', 'Anna', 'Bob', 'Charly', 'Bob'])
b = sorted(np.unique(a))
c = np.arange(len(b))
>>> b
array(['Anna', 'Bob', 'Charly'])
>>> c
array([0, 1, 2])

What I would like to have is an array, d, where the values from a are replaced by their index in b. The expected result should look like this:

>>>d
array([1, 0, 1, 2, 1])

Any suggestions how to get the expected result would be greatly appreciated.

Answer 1

使用以下代码。

d = [b.index(i) for i in a]

Answer 2

No need to create b or c , you can use np.unique and have it return the inverse :

d = np.unique(a, return_inverse = True)[1]                                                           
>>> d
array([1, 0, 1, 2, 1])

For reference:

return_inverse : bool, optional

If True, also return the indices of the unique array (for the specified axis, if provided) that can be used to reconstruct ar.

Alternative pandas solution:

import pandas as pd
pd.Categorical(a).codes
array([1, 0, 1, 2, 1], dtype=int8)

Answer 3

Similar to Avin's answer you can do

a = ['Bob', 'Anna', 'Bob', 'Charly', 'Bob']
b = sorted(list(set(a)))
c = [b.index(x) for x in a]

However, just wanted to add that numpy is a numerical computing library. You can/should just use lists for this.