So verwenden Sie json_normalize zum Parsen von JSON [geschlossen] ⇐ Python

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Hier sieht meine JSON-Datei so aus:

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data = [
{"Ver":0,
"Num":[
{"0":{"A":1,"color": "red",  "C": 9,"date": "2024-12-28"}},
{"1":{"A":5,"color": "blue", "C": 9,"date": "2024-12-29"}},
{"2":{"A":8,"color": "white","C": 9,"date": "2024-12-30"}}
]}
]

Ich habe versucht, json_normalize wie folgt zu verwenden:

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   0.A 0.color  0.C      0.date  1.A 1.color  1.C      1.date  2.A 2.color  \
0  1.0     red  9.0  2024-12-28  NaN     NaN  NaN         NaN  NaN     NaN
1  NaN     NaN  NaN         NaN  5.0    blue  9.0  2024-12-29  NaN     NaN
2  NaN     NaN  NaN         NaN  NaN     NaN  NaN         NaN  8.0   white

2.C      2.date
0  NaN         NaN
1  NaN         NaN
2  9.0  2024-12-30

Erwartetes Ergebnis

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Num   A   color    C    date
0     1   red      9    2024-12-28
1     5   blue     9    2024-12-29
2     5   white    9    2024-12-30

Wie verwende ich es? Danke
wenn sich die Daten[]-Informationen in color.json ändern

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{"Ver":0,
"Num":[
{"0":{"A":1,"color": "red",  "C": 9,"date": "2024-12-28"}},
{"1":{"A":5,"color": "blue", "C": 9,"date": "2024-12-29"}},
{"2":{"A":8,"color": "white","C": 9,"date": "2024-12-30"}}
}

Es gibt mir eine Fehlermeldung

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import json
import pandas as pd

with open('test\\color.json', 'r') as file:
data = json.load(file)
#print(data)
flattened_data = []
for index, item in enumerate(data[0]['Num']):
for key, value in item.items():
flattened_data.append({'Num': int(key), **value})

# Convert to a DataFrame
df = pd.DataFrame(flattened_data)

Wie kann ich es ändern?