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python pandas-解析JSON时出现TypeError:字符串索引必须是整数

typeerror pandas json python

0

P. Prunesquallor · 技术社区 · 8 年前

JSON文件中的记录如下所示(请注意“营养素”是什么样子的):

{
"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。它包括一些争论,并将每种食物的营养成分组合成一张大桌子:

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)

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

*这是本书中的一个例子 Python for Data Analysis

3 回复 | 直到 8 年前

1

Amadan 8 年前

for rec in db 迭代列名 . 要在行上迭代,

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

不过这有点慢(所有需要构造的dict)。 itertuples

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

2

0

zipa 8 年前

代码运行得很好,但是 json

[{
"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}]}]

这是一个只有一条记录的示例。

3

0

P. Prunesquallor 8 年前

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