使用 textblob 对 csv 文件进行情感分析

Question

我对 CSV 文件进行了情感分析，输出打印了句子的极性和主观性。我怎样才能获得 table 格式的输出以及添加到其中的句子分类（正面、负面或中性）？

    import csv
    from textblob import TextBlob

    infile = 'sentence.csv'

    with open(infile, 'r') as csvfile:
        rows = csv.reader(csvfile)
    for row in rows:
        sentence = row[0]
        blob = TextBlob(sentence)
        print (sentence)
        print (blob.sentiment.polarity, blob.sentiment.subjectivity)

我的代码的输出是：

    i am very happy
    1.0 1.0
    its very sad
    -0.65 1.0
    they are bad
    -0.6999999999999998 0.6666666666666666
    hate the life
    -0.8 0.9
    she is so fantastic
    0.4 0.9

提前致谢。

Answer 1

我建议创建一个列表列表并将其导入 pandas 数据框以获得 table 结构

import csv
from textblob import TextBlob
import pandas as pd
import numpy as np

infile = 'sentence.csv'
bloblist = list()

with open(infile, 'r') as csvfile:
    rows = csv.reader(csvfile)

for row in rows:
    sentence = row[0]
    blob = TextBlob(sentence)
    bloblist.append((sentence,blob.sentiment.polarity, blob.sentiment.subjectivity))

这将为您提供一个名为 bloblist 的列表列表将其转换为 pandas 数据框，例如

df = pd.DataFrame(bloblist, columns = ['sentence','sentiment','polarity'])

添加后，您可以像这样创建自定义计算：

df['positive'] = np.where(df.sentiment > .5,1,0)

使用 textblob 对 csv 文件进行情感分析

Sentiment analysis on a csv file using textblob

python

csv

sentiment-analysis

textblob