如何在 Python 中将字典转换为数据框

Question

data = {'documents': [{'score': 0.8806856870651245, 'id': '1'}, {'score': 0.15902310609817505, 'id': '2'}, {'score': 0.9225043058395386, 'id': '3'}, {'score': 0.9872093200683594, 'id': '4'}], 'errors': []}

comments = 
0    I love how we walk in to the fruit and vegetab...
1    When stores upgrade finished nothing to improve??
2    I was pleased with the cheerful efficiency wit...
3    Affordable prices, varieties and staff are ve..

有两部分数据。如何删除 data["errors"] 然后转换为如下所示的数据？在此合并评论数据后，即 Series?

score                        id       comments
0.8806856870651245            1       I love how
0.15902310609817505           2       When stores
0.9225043058395386            3       I was pleased with
0.9872093200683594            4       Affordable prices

Answer 1

你不需要删除错误，你只需要通过访问数据中的 documents 创建数据框。此字典格式将自动转换为数据框，其中列是字典的键。

然后在首先通过 to_frame() 将评论转换为数据框后合并评论。请注意，我使用字符串值作为索引以匹配文档数据中的值。

# Create sample comments.
comments = pd.Series(['I love how', 'When stores', 'I was pleased with', 'Affordable prices'], 
                     index=['1', '2', '3', '4'])

>>> pd.DataFrame(data['documents']).merge(
        comments.to_frame('comments'), left_on='id', right_index=True)
  id     score            comments
0  1  0.880686          I love how
1  2  0.159023         When stores
2  3  0.922504  I was pleased with
3  4  0.987209   Affordable prices

如何在 Python 中将字典转换为数据框

How to convert dictionary to dataframe in Python

python

dictionary

text-analysis

dataframe