python查询数据库内容分类成字典
查询数据库内容：class,name,age,height,sex
当前可获取的是
data=[
{"class":"一班","name":"小明","age":"18",height:"180cm","sex":"男"},
{"class":"一班","name":"小文","age":"17",height:"170cm","sex":"女"},
{"class":"二班","name":"张三","age":"18",height:"180cm","sex":"男"},
{"class":"二班","name":"李四","age":"17",height:"170cm","sex":"女"},
]
如何转成下面我需要的数据
date1=
[
{"class":"一班","info":[{"name":"小明","age":"18",height:"180cm","sex":"男"},{"name":"小文","age":"17",height:"170cm","sex":"女"}]},
{"class":"二班","info":[{"name":"张三","age":"18",height:"180cm","sex":"男"},{"name":"李四","age":"17",height:"170cm","sex":"女"}]}
]
本帖最后由 heign 于 2022-12-14 20:46 编辑
import pandas as pd
df = pd.DataFrame(data)
data1 = []
for i in df['class'].unique():
dct = {}
dct['class'] = i
i_df = df==i]
lst_df = i_df.iloc[:,1:]
d = lst_df.T.to_dict()
dct['info'] = []
for v in d.values():
dct['info'].append(v)
data1.append(dct)
print(data1)
通过pandas肯定还有更简单的方法，但我刚入门写得比较啰嗦 个人拙见，就当一次练手，没有使用第三方库
```
def func(data, column1, column2):
column1_values=[]
for row in data:
value1=row
if value1 not in column1_values:
column1_values.append(value1) #column1_values==["一班", "二班"]
data1=[]
for c1_value in column1_values:
rows=list(filter(lambda row: row==c1_value, data))
c2_value=[]
for r in rows:
r1=r.copy() #直接改rows会导致data变动，因此必须把rows的元素copy到新变量
r1.pop(column1)
c2_value.append(r1)
new_row={column1:c1_value, column2:c2_value}
data1.append(new_row)
return data1
```
```
>>> data=[
{"class":"一班","name":"小明","age":"18","height":"180cm","sex":"男"},
{"class":"一班","name":"小文","age":"17","height":"170cm","sex":"女"},
{"class":"二班","name":"张三","age":"18","height":"180cm","sex":"男"},
{"class":"二班","name":"李四","age":"17","height":"170cm","sex":"女"},
]
>>> data1=func(data, column1="class", column2="info")
>>> print(data1)
[{'class': '一班', 'info': [{'name': '小明', 'age': '18', 'height': '180cm', 'sex': '男'}, {'name': '小文', 'age': '17', 'height': '170cm', 'sex': '女'}]}, {'class': '二班', 'info': [{'name': '张三', 'age': '18', 'height': '180cm', 'sex': '男'}, {'name': '李四', 'age': '17', 'height': '170cm', 'sex': '女'}]}]
```
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