[Python] How do you use list comprehensions in Python for sum of squares in a list?

This is the data provided.

# Data on probability of expansion success by country estimates
success_estimates = {
'Australia': [0.6, 0.33, 0.11, 0.14],
'France': [0.66, 0.78, 0.98, 0.2],
'Italy': [0.6],
'Brazil': [0.22, 0.22, 0.43],
'USA': [0.2, 0.5, 0.3],
'England': [0.45],
'Canada': [0.25, 0.3],
'Argentina': [0.22],
'Greece': [0.45, 0.66, 0.75, 0.99, 0.15, 0.66],
'Morocco': [0.29],
'Tunisia': [0.68, 0.56],
'Egypt': [0.99],
'Jamaica': [0.61, 0.65, 0.71],
'Switzerland': [0.73, 0.86, 0.84, 0.51, 0.99],
'Germany': [0.45, 0.49, 0.36]
}


This is the practice question and a copy of my closest, but non-successful code.

Using list comprehensions, write a script to create a list of lists called sum_squares_list, where each element of the list is a two-item list [country name, value]. The value item in the list should be the sum of squares of that country's success estimates. For example, one element of sum_squares_list should be for Jamaica, where the two-item list is [Jamaica, 1.2987] (since 1.2987 = 0.61^2 + 0.65^2 + 0.71^2).

My Closest but Incorrect Code

sum_squares_list = [[i, sum(success_estimates)] for i in success_estimates]
sum_squares_list

[['Australia', 1.1800000000000002],
['France', 2.62],
['Italy', 0.6],
['Brazil', 0.87],
['USA', 1.0],
['England', 0.45],
['Canada', 0.55],
['Argentina', 0.22],
['Greece', 3.66],
['Morocco', 0.29],
['Tunisia', 1.2400000000000002],
['Egypt', 0.99],
['Jamaica', 1.97],
['Switzerland', 3.9299999999999997],
['Germany', 1.2999999999999998]]


I am having lots of trouble trying to find the sum of squares. Summing all those values is easy enough, but how do I square the elements before I sum it?

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