How to convert nested dictionary to levelled Pandas Dataframe

How to convert more than 3 level N nested dictionary to levelled dataframe?

input_dict = {
                '.Stock': {
                            '.No[0]': '3241512)',
                            '.No[1]': '1111111111',
                            '.No[2]': '444444444444',
                            '.Version': '46',
                            '.Revision': '78'
                          },
                '.Time': '12.11.2022'
             }

what I expect:

import pandas as pd
expected_df = pd.DataFrame([{'level_0': '.Stock', 'level_1': '.No_0', "value": '3241512'},
 {'level_0': '.Stock', 'level_1': '.No_1', "value": '1111111111',},
 {'level_0': '.Stock', 'level_1': '.No_2', "value": '444444444444'},
 {'level_0': '.Stock', 'level_1': '.Version', "value": '46'},
 {'level_0': '.Stock', 'level_1': '.Revision', "value": '78'},
 {'level_0': '.Time',  "value": '12.11.2022'}])

index	level_0	level_1	value
0	.Stock	.No_0	3241512
1	.Stock	.No_1	1111111111
2	.Stock	.No_2	444444444444
3	.Stock	.Version	46
4	.Stock	.Revision	78
5	.Time	NaN	12.11.2022

Firsly I need to convert nested dictionary to list of levelled dictionaries, than lastly convert list of dictionaries to dataframe. How can I convert, pls help me!

I’ve already tried the code below but it doesn’t show exactly the right result.

pd.DataFrame(input_dict).unstack().to_frame().reset_index()

Answer

I found solution, thanks for your comments:(

def nesting_list_convert(in_dict,level=0):
    out_list = []
    for k1, v1 in in_dict.items():
        if isinstance(v1, dict):
            temp_list = nesting_list_convert(v1,level+1)
            for element in temp_list:
                temp_dict = {("level_"+str(level)) : k1}
                temp_dict.update(element)
                out_list.append(temp_dict)
        else:
             out_list.append({("level_"+str(level)) : k1,"value":v1})
return out_list

out_df = pd.DataFrame(nesting_list_convert(input_dict))
out_df = out_df.reindex(sorted(out_df.columns), axis=1)

index	level_0	level_1	value
0	.Stock	.No_0	3241512
1	.Stock	.No_1	1111111111
2	.Stock	.No_2	444444444444
3	.Stock	.Version	46
4	.Stock	.Revision	78
5	.Time	NaN	12.11.2022

This solves 6′ nested level of dictionary.