Hello! Today we will cover one of the frequently asked questions in Python coding tests<\/strong>, which is the problem of finding the minimum number of coins<\/strong>. This problem is particularly helpful in understanding algorithms and greedy problems and can be applied in various situations.<\/p>\n You have various coins, each with a finite quantity. You need to use the minimum number of coins to provide change for a given amount. Given the types of coins and the target amount as input, write a program that outputs the minimum number of coins needed.<\/p>\n Output the minimum number of coins needed to make the target amount.<\/p>\n This problem can be solved using a greedy algorithm. A greedy algorithm is a method of solving a problem by choosing the option that seems best at the moment, aiming to find an optimal solution overall. In this case, we can start by using the highest value coins as much as possible.<\/p>\n Now, let’s implement the Python code based on the above approach. We will write code to count the number of coins based on the given input.<\/p>\n The above code demonstrates the process of using the minimum number of coins based on the entered coin values and target amount. For example, if the coin types are [1, 2, 5]<\/strong> and the target amount is 11<\/strong>, the balance is reduced through the following process:<\/p>\n The time complexity of this algorithm is O(n). Here, n is the number of given coins, and sorting the coin list takes O(n log n). Therefore, the overall time complexity can be considered O(n log n).<\/p>\n One thing to be cautious of when finding the minimum number of coins is when there is no guarantee that coins will always exist. For example, if it is not possible to create the target amount, appropriate messages can be output through exception handling.<\/p>\n I hope this problem has helped enhance your understanding of greedy algorithms. Practice the algorithm by trying various combinations of coins and target amounts. Since this is a common problem in coding tests, it will be very beneficial to be familiar with it.<\/p>\nProblem Description<\/h2>\n
Input Format<\/h3>\n
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Output Format<\/h3>\n
Example Input<\/h2>\n
\n 3 11\n 1 2 5\n <\/pre>\n
Example Output<\/h2>\n
\n 3\n <\/pre>\n
Solution Approach<\/h2>\n
Step-by-Step Approach<\/h3>\n
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Code Implementation<\/h2>\n
\n def min_coins(n, k, coins):\n # Sort coins in descending order.\n coins.sort(reverse=True)\n \n count = 0\n for coin in coins:\n # Calculate the maximum number of current coins that can be used.\n if k == 0:\n break\n count += k \/\/ coin # How many of this coin can be used\n k %= coin # Update the remaining amount\n \n return count\n\n # Input\n n, k = map(int, input().split())\n coins = list(map(int, input().split()))\n\n # Output result\n print(min_coins(n, k, coins))\n <\/pre>\n
Execution Result Analysis<\/h2>\n
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Time Complexity<\/h2>\n
Precautions<\/h2>\n
Conclusion<\/h2>\n