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137 lines
3.7 KiB
Markdown
137 lines
3.7 KiB
Markdown
---
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id: 5e94a54cc7b022105bf0fd2c
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title: 词频
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challengeType: 1
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forumTopicId: 393913
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dashedName: word-frequency
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---
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# --description--
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Given a text string and an integer n, return the n most common words in the file (and the number of their occurrences) in decreasing frequency.
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# --instructions--
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编写一个函数来计算每个单词的出现次数，并返回 n 个最常用的单词以及它们出现频率递减的次数。
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该函数应返回一个二维数组，其中包含以下形式的每个元素：`[word, freq]`。 `word` 应该是单词的小写版本，`freq` 是表示计数的数字。
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如果未提供字符串，该函数应返回一个空数组。
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该函数应该不区分大小写，例如，字符串“Hello”和“hello”应该被视为相同。
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您可以将具有特殊字符（例如下划线、破折号、撇号、逗号等）的单词视为不同的单词。
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例如，给定字符串“Hello hello goodbye”，你的函数应该返回`[['hello', 2], ['goodbye', 1]]`。
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# --hints--
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`wordFrequency` 应该是一个函数。
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```js
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assert(typeof wordFrequency == 'function');
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```
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`wordFrequency` 应该返回一个数组。
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```js
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assert(Array.isArray(wordFrequency('test')));
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```
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`wordFrequency("Hello hello world", 2)` 应该返回`[['hello', 2], ['world', 1]]`
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```js
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assert.deepEqual(wordFrequency(example_1, 2), example_1_solution);
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```
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`wordFrequency("The quick brown fox jumped over the lazy dog", 1)` 应该返回`[['the', 2]]`
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```js
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assert.deepEqual(wordFrequency(example_2, 1), example_2_solution);
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```
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`wordFrequency("Opensource opensource open-source open source", 1)` 应该返回`[['opensource', 2]]`
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```js
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assert.deepEqual(wordFrequency(example_3, 1), example_3_solution);
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```
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`wordFrequency("Apple App apply aPP aPPlE", 3)` 应该返回 `[['app', 2], ['apple', 2], ['apply', 1]]` 或 `[['apple', 2], ['app', 2], ['apply', 1]]`
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```js
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const arr = JSON.stringify(wordFrequency(example_4, 3));
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assert(arr === example_4_solution_a || arr === example_4_solution_b);
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```
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`wordFrequency("c d a d c a b d d c", 4)` 应该返回 `[['d', 4], ['c', 3], ['a', 2], ['b', 1]]`
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```js
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assert.deepEqual(wordFrequency(example_5, 4), example_5_solution);
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```
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`wordFrequency("", 5)` 应该返回 `[]`
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```js
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assert.deepEqual(wordFrequency(example_6, 5), example_6_solution);
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```
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# --seed--
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## --before-user-code--
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```js
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var example_1 = 'Hello hello world';
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var example_1_solution = [['hello', 2], ['world', 1]];
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var example_2 = 'The quick brown fox jumped over the lazy dog';
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var example_2_solution = [['the', 2]];
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var example_3 = 'Opensource opensource open-source open source';
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var example_3_solution = [['opensource', 2]];
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var example_4 = 'Apple App apply aPP aPPlE';
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var example_4_solution_a = "[[\"app\",2],[\"apple\",2],[\"apply\",1]]";
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var example_4_solution_b = "[[\"apple\",2],[\"app\",2],[\"apply\",1]]";
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var example_5 = 'c d a d c a b d d c';
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var example_5_solution = [['d', 4], ['c', 3], ['a', 2], ['b', 1]];
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var example_6 = '';
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var example_6_solution = [];
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```
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## --seed-contents--
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```js
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function wordFrequency(txt, n) {
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}
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```
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# --solutions--
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```js
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function wordFrequency(txt, n) {
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var words = txt.split(/\s+/);
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var wordCount = {};
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words.forEach(word => {
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if (word == '') {
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return;
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}
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const lowerWord = word.toLowerCase();
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wordCount[lowerWord] =
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lowerWord in wordCount ? wordCount[lowerWord] + 1 : 1;
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});
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var wordsArray = [];
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for (let [word, count] of Object.entries(wordCount)) {
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wordsArray.push([word, count]);
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}
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wordsArray.sort((a, b) => {
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if (a[1] !== b[1]) {
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return b[1] - a[1];
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} else if (a[0] !== b[0]) {
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return a[0] < b[0] ? -1 : 1;
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}
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return 0;
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});
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return wordsArray.slice(0, n);
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}
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```
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