迭代json结果，并在pandas dataframe中获得所需的数据。

[
    {"name": "Alice", "age": 30, "city": "New York"},
    {"name": "Bob", "age": 25, "city": "Los Angeles"},
    {"name": "Charlie", "age": 35, "city": "Chicago"}
]

import pandas as pd

# JSON数据
data = [
    {"name": "Alice", "age": 30, "city": "New York"},
    {"name": "Bob", "age": 25, "city": "Los Angeles"},
    {"name": "Charlie", "age": 35, "city": "Chicago"}
]

# 转换为DataFrame
df = pd.DataFrame(data)

# 筛选年龄大于30的数据
filtered_df = df[df['age'] > 30]

print(filtered_df)

from pandas import json_normalize

nested_data = [
    {
        "id": 1,
        "info": {
            "name": "Alice",
            "age": 30,
            "address": {
                "city": "New York",
                "zipcode": "10001"
            }
        }
    },
    # ... 其他数据
]

df = json_normalize(nested_data, sep='_')

df['age'] = df['age'].astype(int)

# 删除包含缺失值的行
df_cleaned = df.dropna()

# 或者填充缺失值
df_filled = df.fillna(0)  # 用0填充