在数据框的每一行中应用textblob [英] Apply textblob in for each row of a dataframe

问题描述

我有一个带有col的数据框，其中有文本.我想应用textblob并计算每一行的情感价值.

i have a data frame with a col which has text. I want to apply textblob and calculate sentiment value for each row.

text                sentiment

这太好了
好电影 很棒的故事

this is great
great movie great story

当我执行以下代码时:

df['sentiment'] = list(map(lambda tweet: TextBlob(tweet), df['text']))

我得到了错误:

TypeError: The `text` argument passed to `__init__(text)` must be a string, not <class 'float'>

如何将textBLob应用于数据帧中col的每一行以获取情绪值?

How do you apply textBLob to each row of a col in a dataframe to get the sentiment value?

推荐答案

您可以使用情感返回一个具有情感(极性，主观性)形式的命名元组.

Sentiment returns a namedtuple of the form Sentiment(polarity, subjectivity).

但是您确定df['text']的每一行都是字符串格式吗?如果不是这样，如果TextBlob无法处理文本，您可以尝试在下面返回None:

But are you sure each row of df['text'] is in string format? If not, you could try below to return None if the text cannot be processed by TextBlob:

def sentiment_calc(text):
    try:
        return TextBlob(text).sentiment
    except:
        return None

df['sentiment'] = df['text'].apply(sentiment_calc)

这篇关于在数据框的每一行中应用textblob的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！