Given some data
给一些数据
In [1]: import numpy as np
In [2]: x = np.array(['a', 'b', 'b', 'a'])
And a sorted index
和一个分类指数
In [3]: i = np.array(['a', 'b'])
I want to find the location of each data entry within the index
我想找到索引中每个数据条目的位置
In [4]: # solution here
array([0, 1, 1, 0])
This is a bit like categoricals. I don't want to use Pandas here. I want to do this on fixed length strings. I need this to be somewhat efficient.
这有点像分类。我不想在这里用熊猫。我想在固定长度的弦上做这个。我需要这个有点效率。
1 个解决方案
#1
5
You could use np.searchsorted:
您可以使用np.searchsorted:
>>> np.searchsorted(i, x)
array([0, 1, 1, 0])
The function finds out the index at which each element of x should be placed in i in order to maintain sorted order.
函数找出x的每个元素应该放在i中的索引，以便保持排序的顺序。
#1
5
You could use np.searchsorted:
您可以使用np.searchsorted:
>>> np.searchsorted(i, x)
array([0, 1, 1, 0])
The function finds out the index at which each element of x should be placed in i in order to maintain sorted order.
函数找出x的每个元素应该放在i中的索引，以便保持排序的顺序。