pandas 为数据框的每一行应用 textblob
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Apply textblob in for each row of a dataframe
提问by user2585048
i have a data frame with a col which has text. I want to apply textblob and calculate sentiment value for each row.
我有一个带有文本的 col 的数据框。我想应用 textblob 并计算每一行的情绪值。
text sentiment
this is great
great movie
great story
这是
一部很棒的电影很棒的故事
When i execute the below code:
当我执行以下代码时：
df['sentiment'] = list(map(lambda tweet: TextBlob(tweet), df['text']))
df['sentiment'] = list(map(lambda tweet: TextBlob(tweet), df['text']))
I get the error:
我收到错误：
TypeError: The `text` argument passed to `__init__(text)` must be a string, not <class 'float'>
How do you apply textBLob to each row of a col in a dataframe to get the sentiment value?
如何将 textBLob 应用于数据帧中 col 的每一行以获取情绪值？
回答by JAV
You can use .apply:
您可以使用.apply：
df['sentiment'] = df['text'].apply(lambda tweet: TextBlob(tweet).sentiment)
Sentiment returns a namedtuple of the form Sentiment(polarity, subjectivity).
Sentiment 返回形式为 Sentiment(polarity, subjectivity) 的命名元组。
But are you sure each row of df['text']is in string format? If not, you could try below to return Noneif the text cannot be processed by TextBlob:
但是你确定每一行df['text']都是字符串格式吗？如果没有，None如果 TextBlob 无法处理文本，您可以尝试在下面返回：
def sentiment_calc(text):
try:
return TextBlob(text).sentiment
except:
return None
df['sentiment'] = df['text'].apply(sentiment_calc)
