使用python重塑数据框中的嵌套json数据以获得所需的输出答案

【问题标题】：reshape nested json data in a dataframe using python to get desired output使用python重塑数据框中的嵌套json数据以获得所需的输出
【发布时间】：2022-08-10 22:27:01
【问题描述】：

您好我正在尝试使用熊猫在数据框中重塑此 json 数据。

      id        categories
1     3ee877e0  [{\"entity_def_id\":\"category\",\"permalink\":\"blockchain\",\"uuid\":\"1fea6201\",\"value\":\"Blockchain\"},{\"entity_def_id\":\"category\",\"permalink\":\"cryptocurrency\",\"uuid\":\"bd082f4d\",\"value\":\"Cryptocurrency\"},{\"entity_def_id\":\"category\",\"permalink\":\"loyalty-programs\",\"uuid\":\"4a45af54\",\"value\":\"Loyalty Programs\"},{\"entity_def_id\":\"category\",\"permalink\":\"marketplace-772d\",\"uuid\":\"772da8fe\",\"value\":\"Marketplace\"},{\"entity_def_id\":\"category\",\"permalink\":\"software\",\"uuid\":\"c08b5441\",\"value\":\"Software\"}]

预期结果

id        entity_def_id  permalink         uuid        value
3ee877e0  category       blockchain        1fea6201    Blockchain
3ee877e0  category       cryptocurrency    bd082f4d    Cryptocurrency
3ee877e0  category       loyalty-programs  4a45af54    Loyalty Programs
3ee877e0  category       marketplace-772d  772da8fe    Marketplace
3ee877e0  category       software          c08b5441    Software

很抱歉没有发布我这样做的尝试，但我是 python 新手，并且已经知道如何在 mongodb 和 dataiku 中执行此操作，只是想知道使用 python 执行此操作的方法。

标签： python pandas dataframe dataiku

【解决方案1】：

您可以尝试explodecategories 列，然后将categories 列中的字典转换为多列

out = (df.explode('categories', ignore_index=True)
       .pipe(lambda df: df.join(pd.DataFrame(df.pop('categories').values.tolist()))))

print(out)

         id entity_def_id         permalink      uuid             value
0  3ee877e0      category        blockchain  1fea6201        Blockchain
1  3ee877e0      category    cryptocurrency  bd082f4d    Cryptocurrency
2  3ee877e0      category  loyalty-programs  4a45af54  Loyalty Programs
3  3ee877e0      category  marketplace-772d  772da8fe       Marketplace
4  3ee877e0      category          software  c08b5441          Software

【讨论】：

【解决方案2】：

您可以获取categories 中的字典列表，按原样将其传递给DataFrame()，然后使用insert 插入您的id 列

import pandas as pd

current_df = pd.DataFrame({"id": "3ee877e0","categories":[[{"entity_def_id":"category","permalink":"blockchain","uuid":"1fea6201","value":"Blockchain"},{"entity_def_id":"category","permalink":"cryptocurrency","uuid":"bd082f4d","value":"Cryptocurrency"},{"entity_def_id":"category","permalink":"loyalty-programs","uuid":"4a45af54","value":"Loyalty Programs"},{"entity_def_id":"category","permalink":"marketplace-772d","uuid":"772da8fe","value":"Marketplace"},{"entity_def_id":"category","permalink":"software","uuid":"c08b5441","value":"Software"}]]})

id_ = current_df.loc[:,"id"].values[0]
categories = current_df.loc[:,"categories"].values[0]

new_df = pd.DataFrame(categories )
new_df.insert(0,"id", id_ )

结果

         id entity_def_id         permalink      uuid             value
0  3ee877e0      category        blockchain  1fea6201        Blockchain
1  3ee877e0      category    cryptocurrency  bd082f4d    Cryptocurrency
2  3ee877e0      category  loyalty-programs  4a45af54  Loyalty Programs
3  3ee877e0      category  marketplace-772d  772da8fe       Marketplace
4  3ee877e0      category          software  c08b5441          Software

【讨论】：