Count frequency of words in a list and sort by frequency

I am using Python 3.3

I need to create two lists, one for the unique words and the other for the frequencies of the word.

I have to sort the unique word list based on the frequencies list so that the word with the highest frequency is first in the list.

I have the design in text but am uncertain how to implement it in Python.

The methods I have found so far use either Counter or dictionaries which we have not learned. I have already created the list from the file containing all the words but do not know how to find the frequency of each word in the list. I know I will need a loop to do this but cannot figure it out.

Here's the basic design:

 original list = ["the", "car",....]
 newlst = []
 frequency = []
 for word in the original list
       if word not in newlst:
           newlst.append(word)
           set frequency = 1
       else
           increase the frequency
 sort newlst based on frequency list 

use this

from collections import Counter
list1=['apple','egg','apple','banana','egg','apple']
counts = Counter(list1)
print(counts)
# Counter({'apple': 3, 'egg': 2, 'banana': 1})

You can use

from collections import Counter

It supports Python 2.7，read more information here

>>>c = Counter('abracadabra')

>>>c.most_common(3)
[('a', 5), ('r', 2), ('b', 2)]

use dict

>>>d={1:'one', 2:'one', 3:'two'}
>>>c = Counter(d.values())
[('one', 2), ('two', 1)]

But, You have to read the file first, and converted to dict.

it's the python docs example,use re and Counter

# Find the ten most common words in Hamlet
>>> import re
>>> words = re.findall(r'\w+', open('hamlet.txt').read().lower())
>>> Counter(words).most_common(10)
[('the', 1143), ('and', 966), ('to', 762), ('of', 669), ('i', 631),
 ('you', 554),  ('a', 546), ('my', 514), ('hamlet', 471), ('in', 451)]

words = file("test.txt", "r").read().split() #read the words into a list.
uniqWords = sorted(set(words)) #remove duplicate words and sort
for word in uniqWords:
    print words.count(word), word

Pandas answer:

import pandas as pd
original_list = ["the", "car", "is", "red", "red", "red", "yes", "it", "is", "is", "is"]
pd.Series(original_list).value_counts()

If you wanted it in ascending order instead, it is as simple as:

pd.Series(original_list).value_counts().sort_values(ascending=True)

Yet another solution with another algorithm without using collections:

def countWords(A):
   dic={}
   for x in A:
       if not x in  dic:        #Python 2.7: if not dic.has_key(x):
          dic[x] = A.count(x)
   return dic

dic = countWords(['apple','egg','apple','banana','egg','apple'])
sorted_items=sorted(dic.items())   # if you want it sorted

One way would be to make a list of lists, with each sub-list in the new list containing a word and a count:

list1 = []    #this is your original list of words
list2 = []    #this is a new list

for word in list1:
    if word in list2:
        list2.index(word)[1] += 1
    else:
        list2.append([word,0])

Or, more efficiently:

for word in list1:
    try:
        list2.index(word)[1] += 1
    except:
        list2.append([word,0])

This would be less efficient than using a dictionary, but it uses more basic concepts.

You can use reduce() - A functional way.

words = "apple banana apple strawberry banana lemon"
reduce( lambda d, c: d.update([(c, d.get(c,0)+1)]) or d, words.split(), {})

returns:

{'strawberry': 1, 'lemon': 1, 'apple': 2, 'banana': 2}

Using Counter would be the best way, but if you don't want to do that, you can implement it yourself this way.

# The list you already have
word_list = ['words', ..., 'other', 'words']
# Get a set of unique words from the list
word_set = set(word_list)
# create your frequency dictionary
freq = {}
# iterate through them, once per unique word.
for word in word_set:
    freq[word] = word_list.count(word) / float(len(word_list))

freq will end up with the frequency of each word in the list you already have.

You need float in there to convert one of the integers to a float, so the resulting value will be a float.

Edit:

If you can't use a dict or set, here is another less efficient way:

# The list you already have
word_list = ['words', ..., 'other', 'words']
unique_words = []
for word in word_list:
    if word not in unique_words:
        unique_words += [word]
word_frequencies = []
for word in unique_words:
    word_frequencies += [float(word_list.count(word)) / len(word_list)]
for i in range(len(unique_words)):
    print(unique_words[i] + ": " + word_frequencies[i])

The indicies of unique_words and word_frequencies will match.

The ideal way is to use a dictionary that maps a word to it's count. But if you can't use that, you might want to use 2 lists - 1 storing the words, and the other one storing counts of words. Note that order of words and counts matters here. Implementing this would be hard and not very efficient.

Try this:

words = []
freqs = []

for line in sorted(original list): #takes all the lines in a text and sorts them
    line = line.rstrip() #strips them of their spaces
    if line not in words: #checks to see if line is in words
        words.append(line) #if not it adds it to the end words
        freqs.append(1) #and adds 1 to the end of freqs
    else:
        index = words.index(line) #if it is it will find where in words
        freqs[index] += 1 #and use the to change add 1 to the matching index in freqs

Here is code support your question is_char() check for validate string count those strings alone, Hashmap is dictionary in python

def is_word(word):
   cnt =0
   for c in word:
    
      if 'a' <= c <='z' or 'A' <= c <= 'Z' or '0' <= c <= '9' or c == '$':
          cnt +=1
   if cnt==len(word):
      return True
  return False
    
def words_freq(s):
  d={}
  for i in s.split():
    if is_word(i):
        if i in d:
            d[i] +=1
        else:
            d[i] = 1
   return d

 print(words_freq('the the sky$ is blue not green'))

for word in original_list:
   words_dict[word] = words_dict.get(word,0) + 1

sorted_dt = {key: value for key, value in sorted(words_dict.items(), key=lambda item: item[1], reverse=True)}

keys = list(sorted_dt.keys())
values = list(sorted_dt.values())
print(keys)
print(values)

the best thing to do is :

def wordListToFreqDict(wordlist):
    wordfreq = [wordlist.count(p) for p in wordlist]
    return dict(zip(wordlist, wordfreq))

then try to : wordListToFreqDict(originallist)