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The problem at hand involves calculating a 'happiness' score based on the intersection of a data set with two other sets, 'set_a' and 'set_b'. The data set is a list of integers, and the happiness score is incremented for each element in the intersection of the data set and 'set_a', and decremented for each element in the intersection of the data set and 'set_b'.
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The solution uses Python's built-in data structures and functions to solve the problem. It first creates a Counter object from the data list, which allows for efficient counting of the occurrences of each integer in the list. It then creates sets from the data list and the input sets 'set_a' and 'set_b'. The intersections of the data set with 'set_a' and 'set_b' are then calculated using the '&' operator. For each integer in the intersection of the data set and 'set_a', the happiness score is incremented by the count of that integer in the data list. Similarly, for each integer in the intersection of the data set and 'set_b', the happiness score is decremented by the count of that integer in the data list. The final happiness score is then printed.
from collections import Counter
n, m = map(int, input().split())
data = list(map(int, input().split()))
data_counter = Counter(data)
data_set = set(data)
set_a = set(map(int, input().split()))
set_b = set(map(int, input().split()))
happiness = 0
for i in data_set & set_a:
happiness += data_counter[i]
for i in data_set & set_b:
happiness -= data_counter[i]
print(happiness)
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