{"id":1047113,"date":"2024-12-31T13:39:42","date_gmt":"2024-12-31T05:39:42","guid":{"rendered":""},"modified":"2024-12-31T13:39:51","modified_gmt":"2024-12-31T05:39:51","slug":"python%e5%a6%82%e4%bd%95%e6%b1%82%e4%b8%80%e5%88%97%e7%9a%84%e5%92%8c","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1047113.html","title":{"rendered":"python\u5982\u4f55\u6c42\u4e00\u5217\u7684\u548c"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-docs.pingcode.com\/wp-content\/uploads\/2024\/12\/3a6d2238-13e1-490c-a491-3d20cc8aa687.webp?x-oss-process=image\/auto-orient,1\/format,webp\" alt=\"python\u5982\u4f55\u6c42\u4e00\u5217\u7684\u548c\" \/><\/p>\n<p><p> \u5728Python\u4e2d\uff0c\u6c42\u4e00\u5217\u7684\u548c\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u5b9e\u73b0\uff0c<strong>\u5305\u62ec\u4f7f\u7528\u5185\u7f6e\u7684sum()\u51fd\u6570\u3001\u4f7f\u7528for\u5faa\u73af\u3001\u4f7f\u7528\u5217\u8868\u89e3\u6790\u4ee5\u53ca\u501f\u52a9NumPy\u5e93<\/strong>\u3002\u5176\u4e2d\uff0c<strong>\u4f7f\u7528\u5185\u7f6e\u7684sum()\u51fd\u6570<\/strong>\u662f\u6700\u5e38\u7528\u4e14\u9ad8\u6548\u7684\u65b9\u6cd5\u3002\u4e0b\u9762\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u5e76\u7ed9\u51fa\u793a\u4f8b\u4ee3\u7801\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528\u5185\u7f6e\u7684sum()\u51fd\u6570<\/h3>\n<\/p>\n<p><p>Python\u63d0\u4f9b\u4e86\u4e00\u4e2a\u5185\u7f6e\u7684sum()\u51fd\u6570\uff0c\u53ef\u4ee5\u76f4\u63a5\u5bf9\u5217\u8868\u3001\u5143\u7ec4\u7b49\u53ef\u8fed\u4ee3\u5bf9\u8c61\u8fdb\u884c\u6c42\u548c\u64cd\u4f5c\u3002\u8fd9\u662f\u6700\u7b80\u6d01\u4e14\u9ad8\u6548\u7684\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u793a\u4f8b\u4ee3\u7801<\/p>\n<p>numbers = [1, 2, 3, 4, 5]<\/p>\n<p>total = sum(numbers)<\/p>\n<p>print(total)  # \u8f93\u51fa 15<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4f7f\u7528sum()\u51fd\u6570\u4e0d\u4ec5\u7b80\u6d01\uff0c\u800c\u4e14\u6548\u7387\u8f83\u9ad8\uff0c\u9002\u5408\u7528\u4e8e\u5927\u591a\u6570\u60c5\u51b5\u4e0b\u7684\u6c42\u548c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><h3>\u4e8c\u3001\u4f7f\u7528for\u5faa\u73af<\/h3>\n<\/p>\n<p><p>\u5982\u679c\u6211\u4eec\u9700\u8981\u5728\u6c42\u548c\u7684\u8fc7\u7a0b\u4e2d\u8fdb\u884c\u4e00\u4e9b\u5176\u4ed6\u64cd\u4f5c\uff0c\u6216\u8005\u53ea\u662f\u4e3a\u4e86\u66f4\u6e05\u695a\u5730\u4e86\u89e3\u6c42\u548c\u7684\u8fc7\u7a0b\uff0c\u53ef\u4ee5\u4f7f\u7528for\u5faa\u73af\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u793a\u4f8b\u4ee3\u7801<\/p>\n<p>numbers = [1, 2, 3, 4, 5]<\/p>\n<p>total = 0<\/p>\n<p>for num in numbers:<\/p>\n<p>    total += num<\/p>\n<p>print(total)  # \u8f93\u51fa 15<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u521d\u59cb\u5316\u4e00\u4e2a\u53d8\u91cftotal\u4e3a0\uff0c\u7136\u540e\u904d\u5386\u5217\u8868\u4e2d\u7684\u6bcf\u4e00\u4e2a\u5143\u7d20\uff0c\u5c06\u5176\u7d2f\u52a0\u5230total\u4e2d\uff0c\u6700\u540e\u8f93\u51fa\u7ed3\u679c\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u4f7f\u7528\u5217\u8868\u89e3\u6790<\/h3>\n<\/p>\n<p><p>\u5217\u8868\u89e3\u6790\uff08List Comprehension\uff09\u662f\u4e00\u79cd\u7b80\u6d01\u7684\u6784\u9020\u5217\u8868\u7684\u65b9\u6cd5\uff0c\u7ed3\u5408sum()\u51fd\u6570\u4e5f\u53ef\u4ee5\u5b9e\u73b0\u5bf9\u4e00\u5217\u7684\u6c42\u548c\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u793a\u4f8b\u4ee3\u7801<\/p>\n<p>numbers = [1, 2, 3, 4, 5]<\/p>\n<p>total = sum([num for num in numbers])<\/p>\n<p>print(total)  # \u8f93\u51fa 15<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u867d\u7136\u8fd9\u79cd\u65b9\u6cd5\u5728\u672c\u8d28\u4e0a\u4e0e\u76f4\u63a5\u4f7f\u7528sum()\u51fd\u6570\u6ca1\u6709\u592a\u5927\u533a\u522b\uff0c\u4f46\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff08\u4f8b\u5982\u9700\u8981\u5bf9\u5143\u7d20\u8fdb\u884c\u7b5b\u9009\uff09\u4f1a\u663e\u5f97\u66f4\u52a0\u65b9\u4fbf\u3002<\/p>\n<\/p>\n<p><h3>\u56db\u3001\u4f7f\u7528NumPy\u5e93<\/h3>\n<\/p>\n<p><p>\u5bf9\u4e8e\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\uff0c\u5c24\u5176\u662f\u6570\u503c\u6570\u636e\uff0cNumPy\u5e93\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u7ec4\u64cd\u4f5c\u529f\u80fd\u3002\u4f7f\u7528NumPy\u53ef\u4ee5\u663e\u8457\u63d0\u9ad8\u8ba1\u7b97\u6548\u7387\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u793a\u4f8b\u4ee3\u7801<\/p>\n<p>import numpy as np<\/p>\n<p>numbers = np.array([1, 2, 3, 4, 5])<\/p>\n<p>total = np.sum(numbers)<\/p>\n<p>print(total)  # \u8f93\u51fa 15<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>NumPy\u7684sum\u51fd\u6570\u5728\u5e95\u5c42\u8fdb\u884c\u4e86\u4f18\u5316\uff0c\u9002\u5408\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u548c\u6570\u636e\u5206\u6790\u7b49\u5bf9\u6027\u80fd\u8981\u6c42\u8f83\u9ad8\u7684\u573a\u666f\u3002<\/p>\n<\/p>\n<p><h3>\u4e94\u3001\u4f7f\u7528pandas\u5e93<\/h3>\n<\/p>\n<p><p>\u5728\u6570\u636e\u5206\u6790\u4e2d\uff0cPandas\u5e93\u662f\u975e\u5e38\u5e38\u7528\u7684\u5de5\u5177\u3002\u5b83\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u793a\u4f8b\u4ee3\u7801<\/p>\n<p>import pandas as pd<\/p>\n<p>data = {&#39;numbers&#39;: [1, 2, 3, 4, 5]}<\/p>\n<p>df = pd.DataFrame(data)<\/p>\n<p>total = df[&#39;numbers&#39;].sum()<\/p>\n<p>print(total)  # \u8f93\u51fa 15<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>Pandas\u7684DataFrame\u7ed3\u6784\u975e\u5e38\u9002\u5408\u5904\u7406\u8868\u683c\u6570\u636e\uff0c\u5e76\u4e14\u5176sum\u51fd\u6570\u53ef\u4ee5\u65b9\u4fbf\u5730\u5bf9\u67d0\u4e00\u5217\u8fdb\u884c\u6c42\u548c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><h3>\u516d\u3001\u4f7f\u7528functools.reduce\u51fd\u6570<\/h3>\n<\/p>\n<p><p>functools\u6a21\u5757\u4e2d\u7684reduce\u51fd\u6570\u53ef\u4ee5\u5b9e\u73b0\u5bf9\u5217\u8868\u7684\u7d2f\u52a0\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u793a\u4f8b\u4ee3\u7801<\/p>\n<p>from functools import reduce<\/p>\n<p>numbers = [1, 2, 3, 4, 5]<\/p>\n<p>total = reduce(lambda x, y: x + y, numbers)<\/p>\n<p>print(total)  # \u8f93\u51fa 15<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u867d\u7136reduce\u51fd\u6570\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\u80fd\u591f\u63d0\u4f9b\u66f4\u7075\u6d3b\u7684\u64cd\u4f5c\uff0c\u4f46\u5176\u53ef\u8bfb\u6027\u4e0d\u5982\u524d\u9762\u51e0\u79cd\u65b9\u6cd5\uff0c\u56e0\u6b64\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u4f7f\u7528\u8f83\u5c11\u3002<\/p>\n<\/p>\n<p><h3>\u4e03\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u901a\u8fc7\u4ee5\u4e0a\u51e0\u79cd\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u5728Python\u4e2d\u6c42\u4e00\u5217\u7684\u548c\u6709\u591a\u79cd\u9014\u5f84\uff0c\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u9002\u7528\u7684\u573a\u666f\u3002<strong>\u4f7f\u7528\u5185\u7f6e\u7684sum()\u51fd\u6570<\/strong>\u662f\u6700\u7b80\u5355\u3001\u76f4\u63a5\u4e14\u9ad8\u6548\u7684\u65b9\u6cd5\uff0c\u9002\u5408\u5927\u591a\u6570\u60c5\u51b5\uff1b<strong>\u4f7f\u7528for\u5faa\u73af<\/strong>\u5219\u80fd\u591f\u5728\u6c42\u548c\u8fc7\u7a0b\u4e2d\u8fdb\u884c\u989d\u5916\u64cd\u4f5c\uff1b<strong>\u5217\u8868\u89e3\u6790<\/strong>\u5728\u9700\u8981\u5bf9\u5143\u7d20\u8fdb\u884c\u7b5b\u9009\u65f6\u663e\u5f97\u975e\u5e38\u65b9\u4fbf\uff1b<strong>NumPy<\/strong>\u5219\u9002\u7528\u4e8e\u5bf9\u6027\u80fd\u8981\u6c42\u8f83\u9ad8\u7684\u6570\u503c\u8ba1\u7b97\uff1b<strong>Pandas<\/strong>\u5728\u6570\u636e\u5206\u6790\u4e2d\u975e\u5e38\u5f3a\u5927\uff1b<strong>functools.reduce<\/strong>\u63d0\u4f9b\u4e86\u4e00\u79cd\u66f4\u7075\u6d3b\u4f46\u4e0d\u592a\u5e38\u7528\u7684\u65b9\u5f0f\u3002<\/p>\n<\/p>\n<p><p>\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u4e0d\u4ec5\u80fd\u63d0\u9ad8\u4ee3\u7801\u7684\u53ef\u8bfb\u6027\u548c\u6548\u7387\uff0c\u8fd8\u80fd\u66f4\u597d\u5730\u6ee1\u8db3\u4e0d\u540c\u7684\u9700\u6c42\u3002\u5e0c\u671b\u901a\u8fc7\u8fd9\u7bc7\u6587\u7ae0\uff0c\u80fd\u591f\u5e2e\u52a9\u4f60\u66f4\u597d\u5730\u7406\u89e3\u548c\u638c\u63e1Python\u4e2d\u6c42\u548c\u64cd\u4f5c\u7684\u5404\u79cd\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u6c42\u4e00\u4e2a\u5217\u8868\u7684\u603b\u548c\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5185\u7f6e\u7684<code>sum()<\/code>\u51fd\u6570\u6765\u8ba1\u7b97\u4e00\u4e2a\u5217\u8868\u7684\u603b\u548c\u3002\u53ea\u9700\u5c06\u5217\u8868\u4f5c\u4e3a\u53c2\u6570\u4f20\u9012\u7ed9<code>sum()<\/code>\u51fd\u6570\uff0c\u4f8b\u5982\uff1a  <\/p>\n<pre><code class=\"language-python\">my_list = [1, 2, 3, 4, 5]\ntotal = sum(my_list)\nprint(total)  # \u8f93\u51fa: 15\n<\/code><\/pre>\n<p>\u8fd9\u6837\u5c31\u53ef\u4ee5\u8f7b\u677e\u5f97\u5230\u5217\u8868\u4e2d\u6240\u6709\u5143\u7d20\u7684\u548c\u3002<\/p>\n<p><strong>\u5728Pandas\u4e2d\u5982\u4f55\u8ba1\u7b97\u6570\u636e\u6846\u4e00\u5217\u7684\u548c\uff1f<\/strong><br \/>\u5982\u679c\u4f60\u4f7f\u7528Pandas\u5e93\u5904\u7406\u6570\u636e\uff0c\u53ef\u4ee5\u901a\u8fc7DataFrame\u7684<code>sum()<\/code>\u65b9\u6cd5\u6765\u8ba1\u7b97\u67d0\u4e00\u5217\u7684\u548c\u3002\u4f8b\u5982\uff1a  <\/p>\n<pre><code class=\"language-python\">import pandas as pd\n\ndata = {&#39;numbers&#39;: [1, 2, 3, 4, 5]}\ndf = pd.DataFrame(data)\ntotal = df[&#39;numbers&#39;].sum()\nprint(total)  # \u8f93\u51fa: 15\n<\/code><\/pre>\n<p>\u8fd9\u79cd\u65b9\u6cd5\u9002\u7528\u4e8e\u5927\u578b\u6570\u636e\u96c6\uff0c\u80fd\u591f\u9ad8\u6548\u5730\u5904\u7406\u6570\u636e\u3002<\/p>\n<p><strong>\u6709\u6ca1\u6709\u5176\u4ed6\u65b9\u6cd5\u53ef\u4ee5\u8ba1\u7b97\u4e00\u5217\u7684\u548c\uff1f<\/strong><br \/>\u9664\u4e86\u4f7f\u7528<code>sum()<\/code>\u51fd\u6570\u548cPandas\u5e93\u4e4b\u5916\uff0c\u8fd8\u53ef\u4ee5\u4f7f\u7528\u5faa\u73af\u6216\u5217\u8868\u63a8\u5bfc\u5f0f\u6765\u624b\u52a8\u8ba1\u7b97\u603b\u548c\u3002\u4f8b\u5982\uff1a  <\/p>\n<pre><code class=\"language-python\">my_list = [1, 2, 3, 4, 5]\ntotal = 0\nfor num in my_list:\n    total += num\nprint(total)  # \u8f93\u51fa: 15\n<\/code><\/pre>\n<p>\u8fd9\u79cd\u65b9\u6cd5\u867d\u7136\u4e0d\u5982\u5185\u7f6e\u51fd\u6570\u7b80\u6d01\uff0c\u4f46\u80fd\u591f\u5e2e\u52a9\u7406\u89e3\u8ba1\u7b97\u8fc7\u7a0b\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u6c42\u4e00\u5217\u7684\u548c\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u5b9e\u73b0\uff0c\u5305\u62ec\u4f7f\u7528\u5185\u7f6e\u7684sum()\u51fd\u6570\u3001\u4f7f\u7528for\u5faa\u73af\u3001\u4f7f\u7528\u5217\u8868\u89e3\u6790\u4ee5 [&hellip;]","protected":false},"author":3,"featured_media":1047134,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1047113"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1047113"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1047113\/revisions"}],"predecessor-version":[{"id":1047140,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1047113\/revisions\/1047140"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1047134"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1047113"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1047113"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1047113"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}