freeCodeCamp/curriculum/challenges/espanol/10-coding-interview-prep/rosetta-code/word-frequency.md

id, title, challengeType, forumTopicId, dashedName

id	title	challengeType	forumTopicId	dashedName
5e94a54cc7b022105bf0fd2c	Frecuencia de palabras	1	393913	word-frequency

--description--

Dada una cadena de texto y un número entero n, devuelve las n palabras más comunes en el archivo (y el número de sus ocurrencias) en una frecuencia decreciente.

--instructions--

Write a function to count the occurrences of each word and return the n most commons words along with the number of their occurrences in decreasing frequency.

La función debe devolver un arreglo 2D con cada uno de los elementos de la siguiente forma: [word, freq]. word debe ser la versión en minúscula de la palabra y freq el número que indica el conteo.

La función debe devolver un arreglo vacío, si no se proporciona ninguna cadena.

La función debe ser insensible a mayúsculas, por ejemplo, las cadenas "Hola" y "hola" deben ser tratadas de la misma manera.

Puede tratar palabras que tienen caracteres especiales como guiones bajos, guiones, apóstrofes, comas, etc., como palabras distintas.

Por ejemplo, dada la cadena "Hello hello goodbye", tu función debe devolver [['hello', 2], ['goodbye', 1]].

--hints--

wordFrequency debe ser una función.

assert(typeof wordFrequency == 'function');

wordFrequency debe devolver un arreglo.

assert(Array.isArray(wordFrequency('test')));

wordFrequency("Hello hello world", 2) debe retornar [['hello', 2], ['world', 1]]

assert.deepEqual(wordFrequency(example_1, 2), example_1_solution);

wordFrequency("The quick brown fox jumped over the lazy dog", 1) debe retornar [['the', 2]]

assert.deepEqual(wordFrequency(example_2, 1), example_2_solution);

wordFrequency("Opensource opensource open-source open source", 1) debería devolver [['opensource', 2]]

assert.deepEqual(wordFrequency(example_3, 1), example_3_solution);

wordFrequency("Apple App apply aPP aPPlE", 3) deberá devolver [['app', 2], ['apple', 2], ['apply', 1]] o [['apple', 2], ['app', 2], ['apply', 1]]

const arr = JSON.stringify(wordFrequency(example_4, 3));
assert(arr === example_4_solution_a || arr === example_4_solution_b);

wordFrequency("c d a d c a b d d c", 4) deberá retornar [['d', 4], ['c', 3], ['a', 2], ['b', 1]]

assert.deepEqual(wordFrequency(example_5, 4), example_5_solution);

wordFrequency("", 5) deberá retornar []

assert.deepEqual(wordFrequency(example_6, 5), example_6_solution);

--seed--

--before-user-code--

var example_1 = 'Hello hello world';
var example_1_solution = [['hello', 2], ['world', 1]];
var example_2 = 'The quick brown fox jumped over the lazy dog';
var example_2_solution = [['the', 2]];
var example_3 = 'Opensource opensource open-source open source';
var example_3_solution = [['opensource', 2]];
var example_4 = 'Apple App apply aPP aPPlE';
var example_4_solution_a = "[[\"app\",2],[\"apple\",2],[\"apply\",1]]";
var example_4_solution_b = "[[\"apple\",2],[\"app\",2],[\"apply\",1]]";
var example_5 = 'c d a d c a b d d c';
var example_5_solution = [['d', 4], ['c', 3], ['a', 2], ['b', 1]];
var example_6 = '';
var example_6_solution = [];

--seed-contents--

function wordFrequency(txt, n) {

}

--solutions--

function wordFrequency(txt, n) {
  var words = txt.split(/\s+/);
  var wordCount = {};
  words.forEach(word => {
    if (word == '') {
      return;
    }
    const lowerWord = word.toLowerCase();
    wordCount[lowerWord] =
      lowerWord in wordCount ? wordCount[lowerWord] + 1 : 1;
  });

  var wordsArray = [];
  for (let [word, count] of Object.entries(wordCount)) {
    wordsArray.push([word, count]);
  }

  wordsArray.sort((a, b) => {
    if (a[1] !== b[1]) {
      return b[1] - a[1];
    } else if (a[0] !== b[0]) {
      return a[0] < b[0] ? -1 : 1;
    }
    return 0;
  });
  return wordsArray.slice(0, n);
}