{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "<h1>122. Best Time to Buy and Sell Stock II</h1>\n", "<hr>\n", "\n", "<!--Copy Paste Leetcode statement between-->\n", "<p>Say you have an array <code>prices</code> for which the <em>i<sup>th</sup></em> element is the price of a given stock on day <em>i</em>.</p>\n", "\n", "<p>Design an algorithm to find the maximum profit. You may complete as many transactions as you like (i.e., buy one and sell one share of the stock multiple times).</p>\n", "\n", "<p><strong>Note:</strong> You may not engage in multiple transactions at the same time (i.e., you must sell the stock before you buy again).</p>\n", "\n", "<p><strong>Example 1:</strong></p>\n", "\n", "<pre><strong>Input:</strong> [7,1,5,3,6,4]\n", "<strong>Output:</strong> 7\n", "<strong>Explanation:</strong> Buy on day 2 (price = 1) and sell on day 3 (price = 5), profit = 5-1 = 4.\n", " Then buy on day 4 (price = 3) and sell on day 5 (price = 6), profit = 6-3 = 3.\n", "</pre>\n", "\n", "<p><strong>Example 2:</strong></p>\n", "\n", "<pre><strong>Input:</strong> [1,2,3,4,5]\n", "<strong>Output:</strong> 4\n", "<strong>Explanation:</strong> Buy on day 1 (price = 1) and sell on day 5 (price = 5), profit = 5-1 = 4.\n", " Note that you cannot buy on day 1, buy on day 2 and sell them later, as you are\n", " engaging multiple transactions at the same time. You must sell before buying again.\n", "</pre>\n", "\n", "<p><strong>Example 3:</strong></p>\n", "\n", "<pre><strong>Input:</strong> [7,6,4,3,1]\n", "<strong>Output:</strong> 0\n", "<strong>Explanation:</strong> In this case, no transaction is done, i.e. max profit = 0.</pre>\n", "\n", "<p> </p>\n", "<p><strong>Constraints:</strong></p>\n", "\n", "<ul>\n", "\t<li><code>1 <= prices.length <= 3 * 10 ^ 4</code></li>\n", "\t<li><code>0 <= prices[i] <= 10 ^ 4</code></li>\n", "</ul>\n", "<!--Copy Paste Leetcode statement between-->\n", "\n", "<p> </p>\n", "<a href=\"https://leetcode.com/problems/best-time-to-buy-and-sell-stock-ii/\">Source</a> \n", "<hr>\n", "\n", "<h4>Code</h4>" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "def max_profit(prices):\n", " profit = 0\n", " for i in range(1, len(prices)):\n", " if prices[i] >= prices[i-1]:\n", " profit += prices[i] - prices[i-1]\n", " return profit" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "def max_profit(prices):\n", " \"\"\"small variation.\"\"\"\n", " profit = 0\n", " for i, price in enumerate(prices[1:], 1): # i starts at 1\n", " if price >= prices[i-1]:\n", " profit += price - prices[i-1]\n", " return profit" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "<h4>Check</h4>" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "7" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "prices = [7,1,5,3,6,4]\n", "max_profit(prices)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "4" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "prices = [1,2,3,4,5]\n", "max_profit(prices)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "prices = [7,6,4,3,1]\n", "max_profit(prices)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "13" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "prices = [4, 6, 3, 8, 0, 6]\n", "max_profit(prices)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "12" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "prices = [4, 12, 0, 4]\n", "max_profit(prices)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.2" } }, "nbformat": 4, "nbformat_minor": 1 }