将嵌套 JSON 转换为 pandas DataFrame

Question

我有一个嵌套的 JSON，我想提取其中的一部分并将其制成 pandas DataFrame。我浏览的任何 stackoverflow 帖子都无法正常工作！

我尝试了使用现有帖子的不同方法，但无法正常工作

来自“结果”的 JSON

 b'{"coin":{"id":363,"name":"Bitcoin","code":"BTC"},"dataType":"marketCap","baseCurrency":"USD","data":[{"date":"2018-01-12","marketCap":"232547809668.32000000"},{"date":"2018-01-13","marketCap":"241311607656.32000000"}

代码：

http = urllib3.PoolManager()
url = 'https://www.cryptocurrencychart.com/api/coin/history/363/2018-01-12/2019-01-12/marketCap/USD'
headers = urllib3.util.make_headers(basic_auth='xxx:xxx')
r = http.request('GET', url , headers = headers) 
result = r.data

df = json_normalize(result['data'])
df.set_index('date', inplace = True)

结果是类型：字节

错误：

TypeError: byte indices must be integers or slices, not str

预期的数据帧

            BTCmarketCap
2019-01-01  xxxxxxx 
2019-01-02  xxxxxx

Answer 1

要解压字典，请使用 json_normalize 和 record_path=... 参数。

import pandas.io.json as pd_json

data = pd_json.loads(result)
pd_json.json_normalize(data, record_path='data')

         date              marketCap
0  2018-01-12  232547809668.32000000
1  2018-01-13  241311607656.32000000

---

如果您还想要其他值，请传递 meta=.... 参数：

df = pd_json.json_normalize(data, 
                            record_path='data', 
                            meta=['coin', 'dataType', 'baseCurrency'])
df

         date              marketCap     ...        dataType baseCurrency
0  2018-01-12  232547809668.32000000     ...       marketCap          USD
1  2018-01-13  241311607656.32000000     ...       marketCap          USD

 df.columns
# Index(['date', 'marketCap', 'coin', 'dataType', 'baseCurrency'], dtype='object')