如何使用字典来翻译/替换数组的元素?

本文介绍了如何使用字典来翻译/替换数组的元素?的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我有一个numpy数组，其中包含数百个大写字母的元素，没有特定顺序

I have a numpy array, which has hundreds of elements which are capital letters, in no particular order

import numpy as np abc_array = np.array(['B', 'D', 'A', 'F', 'H', 'I', 'Z', 'J', ...])

此numpy.ndarray中的每个元素都是一个numpy.string_.

Each element in this numpy.ndarray is a numpy.string_.

我还有一个翻译词典"，其中包含键/值对，以便大写字母对应于城市

I also have a "translation dictionary", with key/value pairs such that the capital letter corresponds to a city

transdict = {'A': 'Adelaide', 'B': 'Bombay', 'C': 'Cologne',...}

字典transdict中只有26对，但是numpy数组中有数百个字母我必须翻译.

There are only 26 pairs in the dictionary transdict, but there are hundreds of letters in the numpy array I must translate.

最有效的方法是什么?

What is the most efficient way to do this?

我已经考虑过使用numpy.core.defchararray.replace(a, old, new, count=None)[source]，但这会返回ValueError，因为numpy数组的大小与字典键/值的大小不同.

I have considered using numpy.core.defchararray.replace(a, old, new, count=None)[source] but this returns a ValueError, as the numpy array is a different size that the dictionary keys/values.

AttributeError: 'numpy.ndarray' object has no attribute 'translate'

推荐答案

这样做会吗?有时，纯Python是处理此类问题的一种好方法.下面将构建翻译列表(轻松转换回numpy数组)和合并的输出.

Will this do? Sometimes, plain Python is a good, direct way to handle such things. The below builds a list of translations (easily converted back to a numpy array) and the joined output.

import numpy as np abc_array = np.array(['B', 'D', 'A', 'F', 'H', 'I', 'Z', 'J']) transdict = {'A': 'Adelaide', 'B': 'Bombay', 'C': 'Cologne', 'D': 'Dresden', 'E': 'Erlangen', 'F': 'Formosa', 'G': 'Gdansk', 'H': 'Hague', 'I': 'Inchon', 'J': 'Jakarta', 'Z': 'Zambia' } phoenetic = [transdict[letter] for letter in abc_array] print ' '.join(phoenetic)

输出为:

Bombay Dresden Adelaide Formosa Hague Inchon Zambia Jakarta