将 CSV 文件的行转换为元组列表？

Question

我有一个 .CSV 文件，其中有两列，一列用于推文，另一列用于格式如下的情绪值（但用于数千条推文）：

I like stackoverflow,Positive
Thanks for your answers,Positive
I hate sugar,Negative
I do not like that movie,Negative
stackoverflow is a question and answer site,Neutral
Python is oop high-level programming language,Neutral

我想得到这样的输出：

negfeats = [('I do not like that movie','Negative'),('I hate sugar','Negative')]
posfeats = [('I like stackoverflow','Positive'),('Thanks for your answers','Positive')]
neufeats = [('stackoverflow is a question and answer site','Neutral'),('Python is oop high-level programming language','Neutral')]

我在下面尝试过这样做，但我在元组中丢失了一些字符。另外，如何将 x、y 和 z 保持为整数而不是浮点数？

import csv
neg = ['Negative']
pos = ['Positive']
neu = ['Neutral']
neg_counter=0
pos_counter=0
neu_counter=0
negfeats = []
posfeats = []
neufeats = []
with open('ff_tweets.csv', 'Ur') as f:
    for k in f:
        if any(word in k for word in neg):
            negfeats = list(tuple(rec) for rec in csv.reader(f, delimiter=','))
            neg_counter+=1
        elif any(word in k for word in pos):
            posfeats = list(tuple(rec) for rec in csv.reader(f, delimiter=','))
            pos_counter+=1
        else:
            neufeats = list(tuple(rec) for rec in csv.reader(f, delimiter=','))
            neu_counter+=1
x = neg_counter * 3/4
y = pos_counter * 3/4
z = neu_counte * 3/4
print negfeats 
print posfeats 
print neufeats 
print x
print y
print z

Answer 1

这应该可以工作

import csv

neg = 'Negative'
pos = 'Positive'
neu = 'Neutral'
negfeats = []
posfeats = []
neufeats = []

with open('ff_tweets.csv', 'Ur') as f:
    for r in csv.reader(f):
        if r[1] == neg:
            negfeats.append((r[0], r[1]))
        if r[1] == pos:
            posfeats.append((r[0], r[1]))
        if r[1] == neu:
            neufeats.append((r[0], r[1]))

x = len(negfeats) * float(3)/4
y = len(posfeats) * float(3)/4
z = len(neufeats) * float(3)/4

print negfeats 
print posfeats 
print neufeats 
print x
print y
print z

Answer 2

使用 Pandas 试试这个。 'Sentiment' 是 csv 文件中的一列：

import pandas as pd

df = pd.read_csv('ff_tweets.csv')

pos = tuple(df.loc[df['Sentiment'] == 'Positive'].apply(tuple, axis = 1))
neu = tuple(df.loc[df['Sentiment'] == 'Neutral'].apply(tuple, axis = 1))
neg = tuple(df.loc[df['Sentiment'] == 'Negative'].apply(tuple, axis = 1))

print pos, neg, neu

输出：

(('I like stackoverflow', 'Positive'), ('Thanks for your answers', 'Positive')) (('I hate sugar', 'Negative'), ('I do not like that movie', 'Negative')) (('stackoverflow is a question and answer site', 'Neutral'), ('Python is oop high-level programming language', 'Neutral'))