How to create a nested dictionary from a dataframe-CodePudding

I have a dataframe like this:

df = pd.DataFrame(id:{1,2,1,4,4},
course:{math,math,sci,art,math},
result:{pass,pass,fail,fail,fail}}

I want to create a nested dictionary like this: for every ID, I want to make a nested dictionary of passed courses and failed courses.

{id:{pass:{courses},fail:{courses}}}

{1:{pass:{math},fail:{sci}},2:{pass:{math}},4:{fail:{art,math}}}

Many thanks

CodePudding user response：

Assuming this input:

   id course result
0   1   math   pass
1   2   math   pass
2   1    sci   fail
3   4    art   fail
4   4   math   fail

You can use nested groupby:

out = (df.groupby('id')
         .apply(lambda g: g.groupby('result')['course']
                           .agg(set).to_dict())
         .to_dict()
       )

output:

{1: {'fail': {'sci'}, 'pass': {'math'}},
 2: {'pass': {'math'}},
 4: {'fail': {'art', 'math'}}}

Or a pivot table:

(df.pivot_table(columns='id', index='result', values='course', aggfunc=set)
   .to_dict()
)

output:

{1: {'fail': {'sci'}, 'pass': {'math'}},
 2: {'fail': nan, 'pass': {'math'}},
 4: {'fail': {'art', 'math'}, 'pass': nan}}

CodePudding user response：

Try this:

df = pd.DataFrame({'id':[1,2,1,4,4],
'course':['math','math','sci','art','math'],
'result':['pass','pass','fail','fail','fail']})


df.groupby(['result', 'id'])['course'].agg(list).unstack().to_dict()

Output:

{1: {'fail': ['sci'], 'pass': ['math']},
 2: {'fail': nan, 'pass': ['math']},
 4: {'fail': ['art', 'math'], 'pass': nan}}

Well, yes, peaking at @mozway solution, use set instead of list:

df.groupby(['result', 'id'])['course'].agg(set).unstack().to_dict()

Output:

{1: {'fail': {'sci'}, 'pass': {'math'}},
 2: {'fail': nan, 'pass': {'math'}},
 4: {'fail': {'art', 'math'}, 'pass': nan}}