[英]How to create a nested JSON from pandas DataFrame?
I am trying to generate a nested JSON from a DataFrame, where attributes of a car are distributed in several rows.我正在尝试从 DataFrame 生成嵌套的 JSON,其中汽车的属性分布在几行中。
cars = {'brand': ['Honda','Toyota','Ford','Audi','Honda','Toyota','Ford','Audi'],
'model': ['Civic','Corolla','Focus','A4','Civic','Corolla','Focus','A4'],
'attributeName': ['color','color','color','color','doors','doors','doors','doors'],
'attributeValue': ['red','blue','black','red',2,4,4,2]
}
df = pd.DataFrame(cars)
At first I grouped the rows and tried to apply the nesting:起初我将行分组并尝试应用嵌套:
df.groupby(['brand','model'])\
.apply(lambda x: x[['attributeName','attributeValue']].to_dict('records'))\
.to_json(orient='records')
[[{"attributeName":"color","attributeValue":"red"},{"attributeName":"doors","attributeValue":2}],[{"attributeName":"color","attributeValue":"black"},{"attributeName":"doors","attributeValue":4}],[{"attributeName":"color","attributeValue":"red"},{"attributeName":"doors","attributeValue":2}],[{"attributeName":"color","attributeValue":"blue"},{"attributeName":"doors","attributeValue":4}]]
[
{
'brand':'Honda',
'model':'Civic',
'attributes':[
{
'name':'color',
'value':'red'
}
]
},
{...}
]
So what can I do to get also the other records and not only the attributes?那么我能做些什么来获取其他记录而不仅仅是属性呢?
In your solution is added rename
with reset_index()
:在您的解决方案中添加了
rename
reset_index()
:
d = {'attributeName':'name','attributeValue':'value'}
j = df.rename(columns=d).groupby(['brand','model']).apply(lambda x: x[['name','value']].to_dict('records')).reset_index(name='attributes').to_json(orient='records')
print (j)
[{"brand":"Audi","model":"A4","attributes":[{"name":"color","value":"red"},{"name":"doors","value":2}]},{"brand":"Ford","model":"Focus","attributes":[{"name":"color","value":"black"},{"name":"doors","value":4}]},{"brand":"Honda","model":"Civic","attributes":[{"name":"color","value":"red"},{"name":"doors","value":2}]},{"brand":"Toyota","model":"Corolla","attributes":[{"name":"color","value":"blue"},{"name":"doors","value":4}]}]
Or:或者:
d = {'attributeName':'name','attributeValue':'value'}
j = df.rename(columns=d).groupby(['brand','model']).apply(lambda x: x[['name','value']].to_dict('records')).explode().apply(lambda x: [x]).reset_index(name='attributes').to_json(orient='records')
print (j)
[{"brand":"Audi","model":"A4","attributes":[{"name":"color","value":"red"}]},{"brand":"Audi","model":"A4","attributes":[{"name":"doors","value":2}]},{"brand":"Ford","model":"Focus","attributes":[{"name":"color","value":"black"}]},{"brand":"Ford","model":"Focus","attributes":[{"name":"doors","value":4}]},{"brand":"Honda","model":"Civic","attributes":[{"name":"color","value":"red"}]},{"brand":"Honda","model":"Civic","attributes":[{"name":"doors","value":2}]},{"brand":"Toyota","model":"Corolla","attributes":[{"name":"color","value":"blue"}]},{"brand":"Toyota","model":"Corolla","attributes":[{"name":"doors","value":4}]}]
df['attributes'] = df.apply(lambda x: [{'name': x['attributeName'], 'value': x['attributeValue']}], axis=1)
df = df.drop(['attributeName','attributeValue'], axis=1)
print (df)
brand model attributes
0 Honda Civic [{'name': 'color', 'value': 'red'}]
1 Toyota Corolla [{'name': 'color', 'value': 'blue'}]
2 Ford Focus [{'name': 'color', 'value': 'black'}]
3 Audi A4 [{'name': 'color', 'value': 'red'}]
4 Honda Civic [{'name': 'doors', 'value': 2}]
5 Toyota Corolla [{'name': 'doors', 'value': 4}]
6 Ford Focus [{'name': 'doors', 'value': 4}]
7 Audi A4 [{'name': 'doors', 'value': 2}]
j = df.to_json(orient='records')
print (j)
[{"brand":"Honda","model":"Civic","attributes":[{"name":"color","value":"red"}]},{"brand":"Toyota","model":"Corolla","attributes":[{"name":"color","value":"blue"}]},{"brand":"Ford","model":"Focus","attributes":[{"name":"color","value":"black"}]},{"brand":"Audi","model":"A4","attributes":[{"name":"color","value":"red"}]},{"brand":"Honda","model":"Civic","attributes":[{"name":"doors","value":2}]},{"brand":"Toyota","model":"Corolla","attributes":[{"name":"doors","value":4}]},{"brand":"Ford","model":"Focus","attributes":[{"name":"doors","value":4}]},{"brand":"Audi","model":"A4","attributes":[{"name":"doors","value":2}]}]
little late but this should give you the desire output:有点晚了,但这应该会给你output的愿望:
d = {'attributeName':'name','attributeValue':'value'} df_cars= (df.rename(columns=d).groupby(['brand','model']).apply(lambda x:x[['name','value']].drop_duplicates().to_dict('records')).reset_index().rename(columns={0:'attributes'})) d = {'attributeName':'name','attributeValue':'value'} df_cars= (df.rename(columns=d).groupby(['brand','model']).apply(lambda x:x [['name','value']].drop_duplicates().to_dict('records')).reset_index().rename(columns={0:'attributes'}))
df_cars.head(10) df_cars.head(10)
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