blocks|key|5561021|text|您可以对此稍作修改，以接受来自文本文件的输入|type|unstyled|depth|inlineStyleRanges|entityRanges|data|5561022|var+letterArray+=+"asdf\njkasdf\nthe\nsadf".split('\n');

function+count(letterArray)+{

++++let+mapping+=+{};

++++for+(let+i=0;+i+<+letterArray.length;+i%2B%2B){
++++++++if+(mapping[letterArray[i]]+!==+undefined){+//+if+the+letter+already+exists+in+the+mapping+increment+it
++++++++++++mapping[letterArray[i]]+%2B=+1;
++++++++}else+{+//if+the+letter+does+not+exist+add+it+and+initialize+it
++++++++++++mapping[letterArray[i]]+=+1;
++++++++}
++++}

++++return+mapping;
}

console.log("count:+",+count(letterArray));|code-block|syntax|javascript|5561023|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

you can modify this a bit for accepting input from a text file

<pre><code>var letterArray = "asdf\njkasdf\nthe\nsadf".split('\n');

function count(letterArray) {

 let mapping = {};

 for (let i=0; i &lt; letterArray.length; i++){
 if (mapping[letterArray[i]] !== undefined){ // if the letter already exists in the mapping increment it
 mapping[letterArray[i]] += 1;
 }else { //if the letter does not exist add it and initialize it
 mapping[letterArray[i]] = 1;
 }
 }

 return mapping;
}

console.log("count: ", count(letterArray));
</code></pre>

blocks|key|1484779|text|我使用python方法得到了您所期望的结果。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1484780|import+numpy+as+np
from+sklearn.feature_extraction.text+import+CountVectorizer

def+wordcount(data):
++++cv+=+CountVectorizer(min_df=0,+strip_accents="ascii",+decode_error+="ignore")

++++counts+=+cv.fit_transform([data]).toarray().ravel()
++++words+=+np.array(cv.get_feature_names())

++++counts+=+map(int,+counts)

++++words+=+[i.tolist()+for+i+in+words]
++++words+=+[x.encode('UTF8')+for+x+in+words]

++++unsorted_result+=+zip(words,+counts)
++++print+sorted(unsorted_result,key=lambda+x:+x[1],+reverse=True)|code-block|syntax|javascript|1484781|将数据作为字符串发送到此函数|1484782|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|K|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|L|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|M|8|@]|9|@]|A|$]]|$1|I|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|J|$]]

I used python approach to get what you expected

<pre><code>import numpy as np
from sklearn.feature_extraction.text import CountVectorizer

def wordcount(data):
 cv = CountVectorizer(min_df=0, strip_accents="ascii", decode_error ="ignore")

 counts = cv.fit_transform([data]).toarray().ravel()
 words = np.array(cv.get_feature_names())

 counts = map(int, counts)

 words = [i.tolist() for i in words]
 words = [x.encode('UTF8') for x in words]

 unsorted_result = zip(words, counts)
 print sorted(unsorted_result,key=lambda x: x[1], reverse=True)
</code></pre>

Send you data as a string to this function

blocks|key|1484812|text|我推荐使用java。它有比javascript更好的工具，但这也可以用javascript完成。将整个列表加载到一个数组中。然后使用sort方法对整个列表进行排序。在js中，它只是.sort()。这将在列表中将相同的单词放在彼此旁边。然后使用循环从上到下遍历这个列表。您将需要两个变量:+lastWord和currentWord。每次单词发生变化时，将最后一个单词放入一个新的数组中，以及您看到它的次数。显然，您还需要一个计数器变量。因此，您将遍历已排序的数组并将结果转储到另一个数组中。您还需要检测何时到达列表末尾的逻辑，以便您可以写入末日世界。这就是你在学校的编程课上经常会遇到的问题。玩得开心。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1484813|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

I'd recommend doing this is java. It has better tools than javascript, but this can also be done in javascript. Load the whole list into an array. Then use a sort method to sort the entire list. In js its just .sort(). This will put words that are the same next to each other in the list. Then use a loop to walk this list from top to bottom. You will need two variables, lastWord and currentWord. Everytime the word changes put the last word into an new array along with how many times you saw it. You'll obviously also need a counter variable. So you'll be walking your sorted array and dumping results into another one. You'll also need logic that detects when you hit the end of the list so you can write the last world. This is the kind of problem that you'll often see in programming classes in school. Have fun.

blocks|key|1775246|text|在Node.js中和在执行npm+i+split2+through2+-S之后|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|1775247|const+fs+=+require('fs')
const+split+=+require('split2')
const+through+=+require('through2')

const+words+=+{}

fs.createReadStream('words.txt')
++.pipe(split())
++.pipe(through(write,+end))


function+write+(buf,+enc,+next)+{
++const+word+=+buf.toString()
++words[word]+=+%2B%2Bwords[word]+%7C%7C+1

++next()
}

function+end+()+{
++Object.keys(words)
++++.sort((a,+b)+=>+words[b]+-+words[a])
++++.forEach(word+=>+{
++++++console.log(`${word}:+${words[word]}+times`)
++++})
}|code-block|syntax|javascript|1775248|entityMap^0|D|O|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@$9|N|A|O|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|P|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|Q|8|@]|D|@]|E|$]]]|L|$]]

In Node.js and after doing <code>npm i split2 through2 -S</code>

<pre><code>const fs = require('fs')
const split = require('split2')
const through = require('through2')

const words = {}

fs.createReadStream('words.txt')
 .pipe(split())
 .pipe(through(write, end))


function write (buf, enc, next) {
 const word = buf.toString()
 words[word] = ++words[word] || 1

 next()
}

function end () {
 Object.keys(words)
 .sort((a, b) =&gt; words[b] - words[a])
 .forEach(word =&gt; {
 console.log(`${word}: ${words[word]} times`)
 })
}
</code></pre>

blocks|key|4092788|text|您可以使用collections模块中的Counter来执行此操作：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4092789|content+=+open("textfile.txt").read()
from+collections+import+Counter
c+=+Counter(content.splitlines())
for+x+in+c.most_common():
++++print("{}:+{}+times".format(x[0],+x[1]))|code-block|syntax|javascript|4092790|用法：|4092791|In+[7]:+contet+=+"""asdf
+++...:+jkasdf
+++...:+the
+++...:+sadf
+++...:+asdn
+++...:+23kl
+++...:+asdf
+++...:+qer
+++...:+f
+++...:+asdf
+++...:+r
+++...:+2
+++...:+r
+++...:+fsd
+++...:+fa
+++...:+sdf
+++...:+asd
+++...:+far2
+++...:+sdv
+++...:+as
+++...:+df
+++...:+asdf
+++...:+asdf"""

In+[8]:+from+collections+import+Counter

In+[9]:+c+=+Counter(content.splitlines())

In+[10]:+c.most_common()
Out[10]:
[('asdf',+5),
+('r',+2),
+('f',+1),
+('23kl',+1),
+('as',+1),
+('df',+1),
+('sadf',+1),
+('qer',+1),
+('sdf',+1),
+('jkasdf',+1),
+('sdv',+1),
+('the',+1),
+('2',+1),
+('fsd',+1),
+('asdn',+1),
+('fa',+1),
+('asd',+1),
+('far2',+1)]|4092792|并遍历c中的结果：|4092793|In+[11]:+for+x+in+c.most_common():
+++....:+++++print("{}:+{}+times".format(x[0],+x[1]))
+++....:
asdf:+5+times
r:+2+times
f:+1+times
23kl:+1+times
as:+1+times
df:+1+times
sadf:+1+times
qer:+1+times
sdf:+1+times
jkasdf:+1+times
sdv:+1+times
the:+1+times
2:+1+times
fsd:+1+times
asdn:+1+times
fa:+1+times
asd:+1+times
far2:+1+times|4092794|entityMap^0|5|B|K|7|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|U|8|@$9|V|A|W|B|C]|$9|X|A|Y|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|Z|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|10|8|@]|D|@]|E|$]]|$1|M|3|N|5|H|7|11|8|@]|D|@]|E|$I|J]]|$1|O|3|P|5|6|7|12|8|@]|D|@]|E|$]]|$1|Q|3|R|5|H|7|13|8|@]|D|@]|E|$I|J]]|$1|S|3|-4|5|6|7|14|8|@]|D|@]|E|$]]]|T|$]]

You can use <code>Counter</code> from <code>collections</code> module for that:

<pre><code>content = open("textfile.txt").read()
from collections import Counter
c = Counter(content.splitlines())
for x in c.most_common():
 print("{}: {} times".format(x[0], x[1]))
</code></pre>

Usage:

<pre><code>In [7]: contet = """asdf
 ...: jkasdf
 ...: the
 ...: sadf
 ...: asdn
 ...: 23kl
 ...: asdf
 ...: qer
 ...: f
 ...: asdf
 ...: r
 ...: 2
 ...: r
 ...: fsd
 ...: fa
 ...: sdf
 ...: asd
 ...: far2
 ...: sdv
 ...: as
 ...: df
 ...: asdf
 ...: asdf"""

In [8]: from collections import Counter

In [9]: c = Counter(content.splitlines())

In [10]: c.most_common()
Out[10]:
[('asdf', 5),
 ('r', 2),
 ('f', 1),
 ('23kl', 1),
 ('as', 1),
 ('df', 1),
 ('sadf', 1),
 ('qer', 1),
 ('sdf', 1),
 ('jkasdf', 1),
 ('sdv', 1),
 ('the', 1),
 ('2', 1),
 ('fsd', 1),
 ('asdn', 1),
 ('fa', 1),
 ('asd', 1),
 ('far2', 1)]
</code></pre>

And loop over the results in c:

<pre><code>In [11]: for x in c.most_common():
 ....: print("{}: {} times".format(x[0], x[1]))
 ....:
asdf: 5 times
r: 2 times
f: 1 times
23kl: 1 times
as: 1 times
df: 1 times
sadf: 1 times
qer: 1 times
sdf: 1 times
jkasdf: 1 times
sdv: 1 times
the: 1 times
2: 1 times
fsd: 1 times
asdn: 1 times
fa: 1 times
asd: 1 times
far2: 1 times
</code></pre>

So I have a file of 100000 words. I'm wondering how I can make it so it creates a file saying "the: 10282 times" "and: 322 times" "sadfas222: 1 times"

This is what the text file look likes:

<pre><code>asdf
jkasdf
the
sadf
asdn
23kl
asdf
qer
f
asdf
r
2
r
fsd
fa
sdf
asd
far2
sdv
as
df
asdf
asdf
</code></pre>

How do I make a word list into an order by most used to least?

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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所以我有一个100000字的文件。我想知道怎样才能创建一个文件，上面写着：“10282次”“和: 322次”"sadfas222: 1次“文本文件如下所示：asdfjkasdfthesadfasdn23klasdfqerfasdfr2rfsdfasdfasdfar2sdvasdfasdfasdf

问如何将单词列表按照最常用到最不常用的顺序排列？
EN

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问如何将单词列表按照最常用到最不常用的顺序排列？EN