如何将原始CSV列、Bigram计数和频率导出到新CSV？

Question

这是我第一次使用Python，如果这是一个愚蠢的问题，我深表歉意。我有一个3列的CSV，第一列叫做comment（这是我处理成bigrams的列），第二列叫做comment type，第三列叫做comment date。我很满意这个代码的当前输出，我将第1列（注释）拆分为bigrams，计算频率，并导出到CSV文件中。但现在，我还想将原始csv中的comment type和comment date列（不做任何更改）添加到word和frequency列旁边的导出csv中。我不知道如何去做，并测试了一些想法，但没有工作。你知道吗

import csv
import string
import re
from nltk.util import everygrams
import pandas as pd


from collections import Counter

from itertools import combinations

df = pd.read_csv('modified.csv', 'r', encoding="utf8",
                 names=['comment'])
top_N = 1000
stopwords = nltk.corpus.stopwords.words('english')

RE_stopwords = r'\b(?:{})\b'.format('|'.join(stopwords))

txt = df.comment.str.lower().str.replace(r'\|', ' ').str.cat(sep=' ')

words = nltk.tokenize.word_tokenize(txt)
words = [w for w in words if not w in RE_stopwords]

bigrm = list(nltk.bigrams(words))



word_dist = nltk.FreqDist([' '.join(x) for x in bigrm])
rslt = pd.DataFrame(word_dist.most_common(top_N),
                columns=['Word', 'Frequency'])

print(rslt)
rslt.to_csv('bigram3.csv')

Answer 1

最后添加的行，在rslt数据帧中创建一个新列，并将数据从原始数据帧复制到这个数据帧。你知道吗

import csv
import string
import re
from nltk.util import everygrams
import pandas as pd


from collections import Counter

from itertools import combinations

df = pd.read_csv('modified.csv', 'r', encoding="utf8",
                 names=['comment'])
top_N = 1000
stopwords = nltk.corpus.stopwords.words('english')

RE_stopwords = r'\b(?:{})\b'.format('|'.join(stopwords))

txt = df.comment.str.lower().str.replace(r'\|', ' ').str.cat(sep=' ')

words = nltk.tokenize.word_tokenize(txt)
words = [w for w in words if not w in RE_stopwords]

bigrm = list(nltk.bigrams(words))



word_dist = nltk.FreqDist([' '.join(x) for x in bigrm])
rslt = pd.DataFrame(word_dist.most_common(top_N),
                columns=['Word', 'Frequency'])
rslt['Column_Type'] = df['comment type']
rslt['Column_Date'] = df['comment date']
print(rslt)
rslt.to_csv('bigram3.csv')