Попытка добавить значения частоты слова в словарь python, который уже имеет ключи, но без значений

Question

любой вход был бы очень признателен. Я долго задерживался на этом и немного отчаялся. Ниже приведена часть моего кода, который должен читать текстовый файл и печатать ключевое слово и количество вхождений этого ключевого слова. Я создал словарь с ключом, но без значений. Когда я пытаюсь добавить значения, я получаю это сообщение об ошибке: «TypeError: индексы списка должны быть целыми или срезами, а не dict». Ошибка для этой строки кода:

position_term = {uat_dic[key_word], word_position}'. 

Я могу ответить на любые вопросы или предоставить дополнительную информацию по мере необходимости. Большое спасибо за любую помощь.

import string 


def main(): 
# Call a function to create the keyword frequency dictionary 
create_keyword_frequency_dictionary() 

# Call a function to calculate the keyword properties: frequency and position 
keyword_frequency, keyword_position = calculate_keyword_properties() 

# Call a function to display the results as in the Sample Output 
display_results(keyword_frequency, keyword_position) 


def create_keyword_frequency_dictionary(): 

# Open the uat_voc.txt file and create a dictionary where 
# the key is the term found in the file, and the value is initialized to 0. 
# This function only initializes the dictionary. 
# Values for the keyword frequencies are set by the calculate_keyword_properties function. 

#easy to use variable name that holds the file path, can easily change the file location here 
file_name = "/Users/ccs/Library/Mobile Documents/com~apple~TextEdit/Documents/uat_voc.txt" 
#create an empty dictionary 
keyword_frequency_dictionary = [] 

#wrap the i/o in a try/catch statement 
try: 
    #open the file and load it into infile 
    infile = open(file_name, 'r') 
    #for each line in infile 
    for line in infile: 
     #take the line, slice off the \n character 
     line = line[:-1] 
     #create a dictionary term where the key is the word in line, initialize value to 0 
     dic_term = {line: 0} 
     #add the dictionary term to the dictionary list 
     keyword_frequency_dictionary.append(dic_term) 

    #close the infile 
    infile.close() 

# Catch IO Errors, with the File Not Found error the primary possible problem to detect. 
except FileNotFoundError: 
    print("File not found when attempting to read", file_name) 
    return None 
except IOError: 
    print("Error in data file when reading", file_name) 
    infile = None 
    infile.close() 
    return None 

return keyword_frequency_dictionary 



def calculate_keyword_properties(): 

    # Open the HowBigDataIsChangingAstronomy.txt' file 
    # Read each line in the file and normalize the text as in Assignment 3 
    # For each word, determine if it is in the keyword_frequency dictionary, i.e, it is a keyword in the UAT vocabulary, 
    # If the word is a UAT keyword, then increment the frequency. 
    # For each word, if it is the first occurrence in the file, then save its position in a keyword_position dictionary 


# Open the HowBigDataIsChangingAstronomy.txt' file 
infile = open('/Users/ccs/Library/Mobile Documents/com~apple~TextEdit/Documents/HowBigDataIsChangingAstronomy.txt','r') 

#read the entire file into clean_file and normalize (this file still has '' instead of ---) length = 2982 
clean_file = remove_punctuation(infile.read()) 

#create empty list that will fill with words 
clean_list_of_words = [] 

#create the keyword dictionary 
uat_dic = create_keyword_frequency_dictionary() 

#create the keyword_position dictionary 
keyword_position_dictionary = [] 

print(clean_file) 
print(len(clean_file)) 
#reparse the file and remove all '' from normalized file (length = 2972) 
for line in clean_file: 
    for word in line.split(): 
     clean_list_of_words.append(word) 

print(len(clean_list_of_words)) 

#iterate through the clean list of words one word at a time to compare; store the word in word_position 
for word_position in clean_list_of_words: 
    #iterate through the dictionary so you can compare the word to each entry 
    for key_word in iter(uat_dic): 
     #IDK what was happening here, i think this is wrong 
     list_word = clean_list_of_words.index(word_position) 
     dic_word = uat_dic.index(key_word) 
     #compare the word from word_position to each key value in the uat_dictionary 
     if list_word == dic_word: 
      #if it was a match, get the value, store it in frequency 
      frequency = uat_dic.index(key_word) 
      #increment frequency 
      frequency+=1 
      #check to see if this was the first occurance of the term 
      if frequency == 1: 
       #if this was the first occurrence, then store a dictionary key/value pair with word_position as the place in the document 
       #uat_dic = {uat_dic[key_word], word_position} 
       position_term = {uat_dic[key_word], word_position} 
       #add the dictionary pair to the key word position list 
       keyword_position_dictionary.append(position_term) 
      #update the frequency value in the uat dictionary 
      uat_dic[key_word] = frequency 
     #keeps looping through for every word in the text document 

#return the uat frequency dictionary and the keyword position dictionary 
return uat_dic, keyword_position_dictionary 


# For each word, determine if it is in the keyword_frequency dictionary, i.e, it is a keyword in the UAT vocabulary, 
# If the word is a UAT keyword, then increment the frequency. 
# For each word, if it is the first occurrence in the file, then save its position in a keyword_position dictionary 

Answer 1

Иногда вы просто должны реорганизовать:

def count_word(file_name, word): 
    return file(file_name).read().count(word) 

Это будет подсчитывать число вхождений word в файле, который является то, что она выглядит, как вы пытаетесь сделать.

Поскольку вы просите посчитать список ключевых слов, что-то вроде этого следует сделать это:

import collections # this is from the standard library 
def count_word(file_name, words): 
    ''' 
    Takes a file name and a list of words to count. 
    ''' 
    # initialize a counter 
    cnt = collections.Counter() 
    # tokenize the file 
    tokens = file(file_name).read().strip().split() 
    for token in tokens: 
     if token in words: 
      # increment the counter for that token 
      cnt[token] += 1 
    return cnt