python pandas-解析JSON时发生TypeError：字符串索引必须为整数

Question

JSON文件中的记录如下所示（请注意“营养素”的外观）：

{
"id": 21441,
"description": "KENTUCKY FRIED CHICKEN, Fried Chicken, EXTRA CRISPY,
Wing, meat and skin with breading",
"tags": ["KFC"],
"manufacturer": "Kentucky Fried Chicken",
"group": "Fast Foods",
"portions": [
{
"amount": 1,
"unit": "wing, with skin",
"grams": 68.0
},
...
],
"nutrients": [
{
"value": 20.8,
"units": "g",
"description": "Protein",
"group": "Composition"
},
{'description': 'Total lipid (fat)',
'group': 'Composition',
'units': 'g',
'value': 29.2}
...
]
}

以下是本书练习*中的代码。 它包括一些争吵，并将每种食物的营养成分汇总到一张大桌子上：

import pandas as pd
import json

db = pd.read_json("foods-2011-10-03.json")

nutrients = []

for rec in db:
     fnuts = pd.DataFrame(rec["nutrients"])
     fnuts["id"] = rec["id"]
     nutrients.append(fnuts)

但是，出现以下错误，我不知道为什么：

---

TypeError                                 Traceback (most recent call last)
<ipython-input-23-ac63a09efd73> in <module>()
      1 for rec in db:
----> 2     fnuts = pd.DataFrame(rec["nutrients"])
      3     fnuts["id"] = rec["id"]
      4     nutrients.append(fnuts)
      5

TypeError: string indices must be integers

*这是《 Python for Data Analysis 》一书中的示例

Answer 1

for rec in db遍历列名 。 要遍历行，

for id, rec in db.iterrows():
    fnuts = pd.DataFrame(rec["nutrients"])
    fnuts["id"] = rec["id"]
    nutrients.append(fnuts)

但是，这有点慢（所有需要构建的字典）。 itertuples更快 但由于您只关心两个序列，因此直接迭代序列可能是最快的：

for id, value in zip(db['id'], db['nutrients']):
    fnuts = pd.DataFrame(value)
    fnuts["id"] = id
    nutrients.append(fnuts)

Answer 2

该代码可以正常工作，但是json应该看起来像这样，代码才能正常工作：

[{
"id": 21441,
"description": "KENTUCKY FRIED CHICKEN, Fried Chicken, EXTRA CRISPY,Wing, meat and skin with breading",
"tags": ["KFC"],
"manufacturer": "Kentucky Fried Chicken",
"group": "Fast Foods",
"portions": [
{"amount": 1,
"unit": "wing, with skin",
"grams": 68.0}],
"nutrients": [{
"value": 20.8,
"units": "g",
"description": "Protein",
"group": "Composition"
},
{'description': 'Total lipid (fat)',
'group': 'Composition',
'units': 'g',
'value': 29.2}]}]

此示例仅包含一个记录。

Answer 3

Amadan回答了这个问题，但是在看到他的回答之前，我设法这样解决了这个问题：

for i in range(len(db)):
    rec = db.loc[i]
    fnuts = pd.DataFrame(rec["nutrients"])
    fnuts["id"] = rec["id"]
    nutrients.append(fnuts)