Question

我有一个这样的数据框，

df
col1    col2    col3
 A       1       2
 B       2       3
 C       4       5
 B       6       7
 B       9       10
 C       11      12
 A       13      14

我需要将其转换为json格式。当我使用to_jon进行转换时，输出是这样的，

{"col1":{"0":"A","1":"B","2":"C","3":"B","4":"B","5":"C","6":"A"},"col2": 
{"0":1,"1":2,"2":4,"3":6,"4":9,"5":11,"6":13},"col3": 
{"0":2,"1":3,"2":5,"3":7,"4":10,"5":12,"6":14}}

但是我正在寻找的json看起来像

{"A":{"col2":[1,13],"col3":[2,14]}, "B":{"col2":[2,6,9],"col3":[3,7,10]}, "C":{"col2": 
[4,11],"col3":[5,12]}}

我正在寻找熊猫快捷方式/ pythonic方法来有效地完成此任务。

Answer 1

尝试使用groupby+transpose：

js = df.groupby('col1').agg(list).T.to_json()
#or df.pivot_table(columns='col1',aggfunc=list).to_json()

print(js)

{"A":{"col2":[1,13],"col3":[2,14]},"B":{"col2":[2,6,9],"col3":[3,7,10]},
 "C":{"col2":[4,11],"col3":[5,12]}}

如何从熊猫数据框创建自定义json

1 个答案: