[英]sentiment analysis of a dataframe using if else statements
我使用这个 function 获得了形容词:
def getAdjectives(text):
blob=TextBlob(text)
return [ word for (word,tag) in blob.tags if tag == "JJ"]
dataset['adjectives'] = dataset['text'].apply(getAdjectives)`
我使用以下代码从 json 文件中获取了 dataframe:
with open('reviews.json') as project_file:
data = json.load(project_file)
dataset=pd.json_normalize(data)
print(dataset.head())
我已经使用以下代码对 dataframe 进行了情绪分析:
dataset[['polarity', 'subjectivity']] = dataset['text'].apply(lambda text: pd.Series(TextBlob(text).sentiment))
print(dataset[['adjectives', 'polarity']])
这是 output:
adjectives polarity
0 [] 0.333333
1 [right, mad, full, full, iPad, iPad, bad, diff... 0.209881
2 [stop, great, awesome] 0.633333
3 [awesome] 0.437143
4 [max, high, high, Gorgeous] 0.398333
5 [decent, easy] 0.466667
6 [it’s, bright, wonderful, amazing, full, few... 0.265146
7 [same, same] 0.000000
8 [old, little, Easy, daily, that’s, late] 0.161979
9 [few, huge, storage.If, few] 0.084762
我试图过滤形容词,以确定这段代码中具有正极性、中性极性和负极性的形容词:
if dataset['polarity']> 0:
print(dataset[['adjectives', 'polarity']], "Positive")
elif dataset['polarity'] == 0:
print(dataset[['adjectives', 'polarity']], "Neutral")
else:
print(dataset[['adjectives', 'polarity']], "Negative")
我得到了错误:
The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
请帮忙。
尝试使用np.select
来确定基于极性的情绪:
df['sentiment'] = np.select(
[
dataset['polarity'] > 0,
dataset['polarity'] == 0
],
[
"Positive",
"Neutral"
],
default="Negative"
)
单线:
df['sentiment'] = np.select([dataset['polarity'] > 0, dataset['polarity'] == 0], ["Positive", "Neutral"], "Negative")
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