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Commitdd45619

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Add alternate election challenge solution
1 parente6a93b3 commitdd45619

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3 files changed

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‎ch08-conditional-logic/9-challenge-simulate-an-election.py

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# 8.9 - Challenge: Simulate an Election
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# Solution to challenge
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# Simulate the results of an election using a Monte Carlo simulation
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fromrandomimportrandom
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num_times_A_wins=0
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num_times_B_wins=0
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num_trials=10_000
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fortrialinrange(0,num_trials):
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votes_for_A=0
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votes_for_B=0
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# Determine who wins the 1st region
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ifrandom()<0.87:
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votes_for_A=votes_for_A+1
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else:
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votes_for_B=votes_for_B+1
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# Determine who wins the 2nd region
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ifrandom()<0.65:
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votes_for_A=votes_for_A+1
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else:
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votes_for_B=votes_for_B+1
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# Determine who wins the erd region
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ifrandom()<0.17:
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votes_for_A=votes_for_A+1
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else:
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votes_for_B=votes_for_B+1
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# Determine overall election outcome
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ifvotes_for_A>votes_for_B:
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num_times_A_wins=num_times_A_wins+1
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else:
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num_times_B_wins=num_times_B_wins+1
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print(f"Probability A wins:{num_times_A_wins/num_trials}")
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print(f"Probability B wins:{num_times_B_wins/num_trials}")
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# 8.9 - Challenge: Simulate an Election
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# Alternate solution to challenge
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# Simulate the results of an election using a Monte Carlo simulation
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fromrandomimportrandom
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defrun_regional_election(chance_A_wins):
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"""Return the result of a regional election, either "A" or "B".
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The chances of "A" winning are determined by chance_A_wins.
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"""
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ifrandom()<chance_A_wins:
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return"A"
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else:
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return"B"
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defrun_election(regional_chances):
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"""Return the result of an election, either "A" or "B".
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regional_chances is a list or tuple of floats representing the
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chances that candidate "A" will win in each region.
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For example, run_election([.2, .5, .7]) will run an election with
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three regions, where candidate "A" has a 20% chance to win in the
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first region, 50% in the second, and 70% in the third.
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"""
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num_regions_won_by_A=0
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forchance_A_winsinregional_chances:
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ifrun_regional_election(chance_A_wins)=="A":
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num_regions_won_by_A=num_regions_won_by_A+1
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# Return the results. Note that the number of regions won by candidate
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# "B" is the total number of regions minus the number of regions won by
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# candidate "A". The total number of regions is the same as the length
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# of the regional_chances list.
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ifnum_regions_won_by_A>len(regional_chances)-num_regions_won_by_A:
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return"A"
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else:
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return"B"
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CHANCES_A_WINS_BY_REGION= [0.87,0.65,0.17]
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NUM_TRIALS=10_000
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# Run the Monte-Carlo simulation
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num_times_A_wins=0
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fortrialinrange(NUM_TRIALS):
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ifrun_election(CHANCES_A_WINS_BY_REGION)=="A":
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num_times_A_wins=num_times_A_wins+1
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# Display the probabilities that candidate A or candidate B wins the
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# election. Note the probability that B wins can be calculated by
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# subtracting the probability that A wins from 1.
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print(f"Probability A wins:{num_times_A_wins/num_trials}")
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print(f"Probability B wins:{1- (num_times_A_wins/num_trials)}")

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