I don’t think think there is anything built-in to pandas to create a nested dictionary of the data. Below is some code that should work in general for a series with a MultiIndex, using a defaultdict
The nesting code iterates through each level of the MultIndex, adding layers to the dictionary until the deepest layer is assigned to the Series value.
In [99]: from collections import defaultdict
In [100]: results = defaultdict(lambda: defaultdict(dict))
In [101]: for index, value in grouped.itertuples():
...: for i, key in enumerate(index):
...: if i == 0:
...: nested = results[key]
...: elif i == len(index) - 1:
...: nested[key] = value
...: else:
...: nested = nested[key]
In [102]: results
Out[102]: defaultdict(<function <lambda> at 0x7ff17c76d1b8>, {2010: defaultdict(<type 'dict'>, {'govnr': {'pati mara': 500.0, 'jess rapp': 80.0}, 'mayor': {'joe smith': 100.0, 'jay gould': 12.0}})})
In [106]: print json.dumps(results, indent=4)
{
"2010": {
"govnr": {
"pati mara": 500.0,
"jess rapp": 80.0
},
"mayor": {
"joe smith": 100.0,
"jay gould": 12.0
}
}
}