Question

因此，我尝试从.txt文件中提取最常用的词，然后将4个最常用的词放入csv文件中。（然后在需要时附加），此刻它正在提取最常用的单词，并附加到一个csv文件中。但这是将每个字母附加到一个单元格上。

python

import collections
import pandas as pd
import matplotlib.pyplot as plt
import csv   
fields=['first','second','third']


# Read input file, note the encoding is specified here 
# It may be different in your text file
file = open('pyTest.txt', encoding="utf8")
a= file.read()
# Stopwords
stopwords = set(line.strip() for line in open('stopwords.txt'))
stopwords = stopwords.union(set(['mr','mrs','one','two','said']))
# Instantiate a dictionary, and for every word in the file, 
# Add to the dictionary if it doesn't exist. If it does, increase the count.
wordcount = {}
# To eliminate duplicates, remember to split by punctuation, and use case demiliters.
for word in a.lower().split():
    word = word.replace(".","")
    word = word.replace(",","")
    word = word.replace(":","")
    word = word.replace("\"","")
    word = word.replace("!","")
    word = word.replace("â€œ","")
    word = word.replace("â€˜","")
    word = word.replace("*","")
    if word not in stopwords:
        if word not in wordcount:
            wordcount[word] = 1
        else:
            wordcount[word] += 1
# Print most common word
n_print = int(input("How many most common words to print: "))
print("\nOK. The {} most common words are as follows\n".format(n_print))
word_counter = collections.Counter(wordcount)
for word in word_counter.most_common(n_print):

    print(word[0])

# Close the file

file.close()

with open('old.csv', 'a') as out_file:
        writer = csv.writer(out_file)
        for word in word_counter.most_common(4):
            print(word)
            writer.writerow(word[0])

输出csv文件

p,i,p,e

d,i,a,m,e,t,e,r

f,i,t,t,i,n,g,s

o,u,t,s,i,d,e

Answer 1

您可以使用生成器表达式将descriptor_scores = numpy.genfromtxt([s[37:] for s in open("results.out")], usecols=(0,1,2,3), max_rows=25)方法返回的列表中每个子列表的第一项提取为一行：

most_common

提取最常用的单词，然后使用python

1 个答案: