3
我有以下数据,我需要做的是应用聚合函数,然后是groupby。如何将熊猫系列转换为所需的JSON格式?
我的数据如下:data.csv
id,category,sub_category,count
0,x,sub1,10
1,x,sub2,20
2,x,sub2,10
3,y,sub3,30
4,y,sub3,5
5,y,sub4,15
6,z,sub5,20
在这里,我试图让通过子类的计数明智的。之后,我需要以JSON格式存储结果。以下代码可以帮助我实现这一目标。 test.py
import pandas as pd
df = pd.read_csv('data.csv')
sub_category_total = df['count'].groupby([df['category'], df['sub_category']]).sum()
print sub_category_total.reset_index().to_json(orient = "records")
上面的代码给了我下面的格式。
[{"category":"x","sub_category":"sub1","count":10},{"category":"x","sub_category":"sub2","count":30},{"category":"y","sub_category":"sub3","count":35},{"category":"y","sub_category":"sub4","count":15},{"category":"z","sub_category":"sub5","count":20}]
但是,我想要的格式如下:
{
"x":[{
"sub_category":"sub1",
"count":10
},
{
"sub_category":"sub2",
"count":30}],
"y":[{
"sub_category":"sub3",
"count":35
},
{
"sub_category":"sub4",
"count":15}],
"z":[{
"sub_category":"sub5",
"count":20}]
}
通过下面的讨论@How to convert pandas DataFrame result to user defined json format,我更换了最后两行的test.py
用,
g = df.groupby('category')[["sub_category","count"]].apply(lambda x: x.to_dict(orient='records'))
print g.to_json()
它给我以下输出。
{"x":[{"count":10,"sub_category":"sub1"},{"count":20,"sub_category":"sub2"},{"count":10,"sub_category":"sub2"}],"y":[{"count":30,"sub_category":"sub3"},{"count":5,"sub_category":"sub3"},{"count":15,"sub_category":"sub4"}],"z":[{"count":20,"sub_category":"sub5"}]}
虽然上述结果有点类似我想要的格式,我不能在这里,因为它会引发错误说执行任何聚合功能。因此,我最终得到了数据文件中的所有行。
有人能帮我实现上面的JSON格式吗?
我尝试了两次投票...它不会让我。 – piRSquared
谢谢。顺便说一句,非常好[问题](http://meta.stackoverflow.com/questions/323414/incentivizing-people-to-avoid-gamesmanship)。 ;) – jezrael
哇!太棒了!非常感谢你@jezrael :) –