Python:json规范化“字符串索引必须为整数"错误

问题描述

在以下代码中，我收到"TypeError:字符串索引必须为整数"的类型错误.

I am getting a type error as "TypeError: string indices must be integers" in the following code.

import pandas as pd
import json
from pandas.io.json import json_normalize

full_json_df = pd.read_json('data/world_bank_projects.json')
json_nor = json_normalize(full_json_df, 'mjtheme_namecode')
json_nor.groupby('name')['code'].count().sort_values(ascending=False).head(10)

Output:
TypeError
Traceback (most recent call last)
<ipython-input-28-9401e8bf5427> in <module>()
      1 # Find the top 10 major project themes (using column 'mjtheme_namecode')
      2
----> 3 json_nor = json_normalize(full_json_df, 'mjtheme_namecode')
      4 #json_nor.groupby('name')['code'].count().sort_values(ascending = False).head(10)
TypeError: string indices must be integers

推荐答案

根据熊猫文档，用于方法json_normalize的data参数:

According to pandas documentation, for data argument of the method json_normalize :

在上面，pd.read_json返回dataframe.因此，您可以尝试使用.to_dict()将dataframe转换为dictionary.使用 to_dict().

In above, pd.read_json returns dataframe.So, you can try converting dataframe to dictionary using .to_dict(). There are various options for using to_dict() as well.

可能类似于以下内容:

json_normalize(full_json_df.to_dict(), ......)

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