我想将来自以下 API 响应的数据解析为 pandas 数据帧。我猜这个 JSON 文件中有一个额外的父级导致了问题。如何删除它并正确解析数据？
网址：“https://api.covid19india.org/state_district_wise.json”
import pandas as pd
URL = "https://api.covid19india.org/state_district_wise.json"
df = pd.read_json(URL)
df.head()
上面的代码不起作用并给出了错误的输出。请帮忙。
【问题讨论】：
在 python 中解析嵌套结构很痛苦，这是适用于您的数据的解决方案：
import requests
URL = "https://api.covid19india.org/state_district_wise.json"
d = requests.get(URL).json()
L = []
for k, v in d.items():
for k1, v1 in v.items():
if isinstance(v1, dict):
for k2, v2 in v1.items():
if isinstance(v2, dict):
for k3, v3 in v2.items():
if isinstance(v3, dict):
d1 = {f'{k3}.{k4}': v4 for k4, v4 in v3.items()}
d2 = {'districtData':k,'State':k2,'statecode': v['statecode']}
d3 = {**d2, **v2, **d1}
del d3[k3]
L.append(d3)
df = pd.DataFrame(L)
print (df)
districtData State statecode \
0 State Unassigned Unassigned UN
1 Andaman and Nicobar Islands Nicobars AN
2 Andaman and Nicobar Islands North and Middle Andaman AN
3 Andaman and Nicobar Islands South Andaman AN
4 Andaman and Nicobar Islands Unknown AN
.. ... ... ...
767 West Bengal Purba Bardhaman WB
768 West Bengal Purba Medinipur WB
769 West Bengal Purulia WB
770 West Bengal South 24 Parganas WB
771 West Bengal Uttar Dinajpur WB
notes active confirmed \
0 0 0
1 District-wise numbers are out-dated as cumulat... 0 0
2 District-wise numbers are out-dated as cumulat... 0 1
3 District-wise numbers are out-dated as cumulat... 19 51
4 148 4442
.. ... ... ...
767 618 8773
768 1424 16548
769 350 5609
770 1899 27445
771 358 5197
deceased recovered delta.confirmed delta.deceased delta.recovered
0 0 0 0 0 0
1 0 0 0 0 0
2 0 1 0 0 0
3 0 32 0 0 0
4 60 4234 0 0 0
.. ... ... ... ... ...
767 74 8081 0 0 0
768 212 14912 0 0 0
769 33 5226 0 0 0
770 501 25045 0 0 0
771 55 4784 0 0 0
[772 rows x 11 columns]
【讨论】：