Pandas extract hierarchical info? - pandas

Question

I have a dataframe which describes serial numbers of items arranged in boxes:
df=pd.DataFrame({'barcode':['1000']*3+['2000']*4+['3000']*3, 'box_number': ['10']*2+['11']+['12']*4+['13','14','15'],'serials': map(str,range(800,810))})
barcode box_number serials
0 1000 10 800
1 1000 10 801
2 1000 11 802
3 2000 12 803
4 2000 12 804
5 2000 12 805
6 2000 12 806
7 3000 13 807
8 3000 14 808
9 3000 15 809
I want to group them hierarchically to output to hierarchical XML, so that every barcode has a list of box numbers which each have list of serials in them.
So I did a groupby which seems to do exactly what I want:
df.groupby(['barcode','box_number'])['serials'].apply(' '.join)
barcode box_number
1000 10 800 801
11 802
2000 12 803 804 805 806
3000 13 807
14 808
15 809
Name: serials, dtype: object
Now, I want to extract this info practically the way it is displayed so that I get a row for each barcode with data grouped similar to this:
row['1000']== {'10': '800 801','11':'802'}
row['2000']== {'12': '803 804 805 806'}
row['3000']== {'13': '807','14':'808','15':'809' }
But I can't seem to figure out how to get this done. I tried reset_index(), another groupby() -- but this doesn't work on existing result as it is a Series, but I can't seem to be able to understand the right way.
How should I this most concisely? I looked over questions here, but didn't seem to find similar issue.

Answer 1

Use dictionary comrehension for get nested dictonary with Series.xs and Series.to_dict:
s = df.groupby(['barcode','box_number'])['serials'].apply(' '.join)
d = {lev: s.xs(lev).to_dict() for lev in s.index.levels[0]}
print (d)
{'1000': {'10': '800 801', '11': '802'},
'2000': {'12': '803 804 805 806'},
'3000': {'13': '807', '14': '808', '15': '809'}}