I need a little help. I want to convert from dataframe into nested dictionaries.
A B C
0 1 0 1.5
1 1 3,2 6.09
2 1 4 7.9
3 2 5 9.5
4 2 0 1.2
5 3 3 2.4
and i want to convert in this format:
dict={1:[{'0':1.5},{'3,2':6.09},{'4':7.9}],2:[{'5':9.5},{'0':1.2}],3:[{'3',2.4}]}
We can do groupby with agg dict items
d = df.set_index('B').groupby('A').agg(lambda x : [{k:v} for k, v in dict(x).items()])['C'].to_dict()
Out[574]:
{1: [{'0': 1.5}, {'3,2': 6.09}, {'4': 7.9}],
2: [{'5': 9.5}, {'0': 1.2}],
3: [{'3': 2.4}]}
This will give you a dictionary, remember dict is a key work in python so you have to use other variable name instead of dict. Here I used dict1.
dict1 = {1:[{'0':1.5, '3,2':6.09,'4':7.9}],2:[{'5':9.5,'0':1.2}],3:[{'3',2.4}]}
pretty similar to this solution:
df = df.set_index('B').groupby('A').apply(lambda x: [x['C'].to_dict()]).to_dict()
print(df)
'''
{1: [{'0': 1.5, '3,2': 6.09, '4': 7.9}],
2: [{'5': 9.5, '0': 1.2}],
3: [{'3': 2.4}]}
