我相信使用for循环解析JSON会收到以下输出。我想知道如何将输出转换为数据框
01E8jn7u387ZHexw2mOo => {'email': 'a4@yahoo.com ',
'agreed_to_terms': True, 'toy_duration': 2, 'dog_name': 'Oakley',
'dog_breeds': ['Mixed Breed / Mutt'], 'zip': '95355', 'human_name':
'Alina'}
01WCbRaNLVVWglHopTEJ => {'zip': '45014', 'human_name': 'Neil',
'agreed_to_terms': True, 'email': 'Nek@gmail.com ',
'toy_duration': 0, 'dog_name': 'Maize, Georgie', 'dog_breeds': ['German
Shorthaired Lab', 'Shih Tzu']}
02InTOWJSxfjHIPDTPdE => {'agreed_to_terms': True, 'email':
'2@aol.com', 'toy_duration': 2, 'dog_name': 'Chewie',
'dog_breeds': ['Shih Tzu'], 'zip': '32068', 'human_name': 'Amber'}
任何帮助将不胜感激。谢谢
答案 0 :(得分:0)
看起来像是json_normalize的工作。
import json
from pandas.io.json import json_normalize
a = {'email': 'a4@yahoo.com ',
'agreed_to_terms': True, 'toy_duration': 2, 'dog_name': 'Oakley',
'dog_breeds': ['Mixed Breed / Mutt'], 'zip': '95355', 'human_name':
'Alina'}
df_a = json_normalize(a)
答案 1 :(得分:0)
您的意思是这样吗?
>>> data = [
{
"email": "a4@yahoo.com ",
"agreed_to_terms": True,
"toy_duration": 2,
"dog_name": "Oakley",
"dog_breeds": ["Mixed Breed / Mutt"],
"zip": "95355",
"human_name": "Alina",
},
{
"zip": "45014",
"human_name": "Neil",
"agreed_to_terms": True,
"email": "Nek@gmail.com ",
"toy_duration": 0,
"dog_name": "Maize, Georgie",
"dog_breeds": ["German Shorthaired Lab", "Shih Tzu"],
},
{
"agreed_to_terms": True,
"email": "2@aol.com",
"toy_duration": 2,
"dog_name": "Chewie",
"dog_breeds": ["Shih Tzu"],
"zip": "32068",
"human_name": "Amber",
},
]
>>> pd.DataFrame(data)
agreed_to_terms dog_breeds dog_name email human_name toy_duration zip
0 True [Mixed Breed / Mutt] Oakley a4@yahoo.com Alina 2 95355
1 True [German Shorthaired Lab, Shih Tzu] Maize, Georgie Nek@gmail.com Neil 0 45014
2 True [Shih Tzu] Chewie 2@aol.com Amber 2 32068
积累一条狗的清单,很容易将其变成熊猫数据框。