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如何通过访问数据框而不是python中的csv进行情感分析？

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我试图了解如何将csv逻辑应用于脚本中已经存在的数据帧输出。

对csv的情感分析

cellForRowAtIndexPath

我有一个数据框，其中有4列，其中一列有成绩单

import pandas as pd
import csv
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer

with open('After.csv',"r",errors='ignore') as f:
    reader = csv.reader(f)
    your_list = list(reader)

analyser = SentimentIntensityAnalyzer()

def print_sentiment_scores(alist):
    for aSentence in alist: 
      asnt = analyser.polarity_scores(aSentence[0])
      print(str(asnt))

df_before = print_sentiment_scores(your_list)

print_sentiment_scores(your_list)


def print_sentiment_scores(alist):
    polarity_scores = []
    for aSentence in alist: 
        asnt = analyser.polarity_scores(aSentence[0])
        print(str(asnt))
        polarity_scores += [asnt]

    return polarity_scores

output_df = pd.DataFrame(print_sentiment_scores(your_list))
output_df.to_csv('some_name.csv')

[353行x 5列] 

test3
Out[52]: 
     confidence  ... speaker
0          0.86  ...       0
1          0.91  ...       0
2          0.94  ...       0
3          0.86  ...       0
4          0.99  ...       0

如何将我上面的情感分析脚本应用于test3数据框中的此特定列（笔录）？

qqaq99 回答：如何通过访问数据框而不是python中的csv进行情感分析？

使用to_list()转换列并应用您的函数，在此示例中，由于您不提供示例数据，因此我使用了函数'f'。

import pandas as pd

df = pd.DataFrame({'A': ['aba','flower'],'B': ['we search stackoverflow','good question']})
print('Print dataframe content:',df)


def print_sentiment_scores(x):
    return x +' '+ x

print()
for word in (df['B'].to_list()):
    print("Print output of the function applied to series:",print_sentiment_scores(word))

出局：

Print dataframe content:         A                        B
0     aba  we search stackoverflow
1  flower            good question

Print output of the function applied to series: we search stackoverflow we search stackoverflow
Print output of the function applied to series: good question good question

here is simple interactive example

dataframepandassentiment-analysisvader
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