[FIXED] Create nested dictionary from a pandas dataframe

Issue

I have this table:

Team	X or Y	Percentage
A	X	80%
A	Y	20%
B	X	70%
B	Y	30%
C	X	60%
C	Y	40%

I want to create a nested dictionary out of this so that if I input the team name and input X or Y, I get the percentage as a return value.

In Python I used the .tolist() method to create lists out of each individual column.

My initial strategy was to create a dict out of the second two columns dict_1 = dict(zip(list2, list3)) and then dict_2 = dict(zip(list1, dict_1)) but that didn't work out because column "X or Y", for example, has similar values, and dictionary keys cannot have repeated values.

The output I had in mind was

{'A':{'X':80%, 'Y':20%}, 'B':{'X':70%,'Y':30%}, ...}

How would I create this? Is there a better way to do this?

Solution

Use pd.DataFrame.pivot:

>>> df.pivot(columns='Team', index='X or Y', values='Percentage').to_dict()
{'A': {'X': '80%', 'Y': '20%'}, 'B': {'X': '70%', 'Y': '30%'}, 'C': {'X': '60%', 'Y': '40%'}}

Answered By - erip