{"id":1055389,"date":"2024-12-31T14:50:12","date_gmt":"2024-12-31T06:50:12","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1055389.html"},"modified":"2024-12-31T14:50:15","modified_gmt":"2024-12-31T06:50:15","slug":"python%e6%95%b0%e6%8d%ae%e6%a1%86%e5%a6%82%e4%bd%95%e5%8a%a0%e4%b8%80%e5%88%97","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1055389.html","title":{"rendered":"python\u6570\u636e\u6846\u5982\u4f55\u52a0\u4e00\u5217"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-docs.pingcode.com\/wp-content\/uploads\/2024\/12\/226b118c-2028-4f68-87d5-889eb1408d63.webp?x-oss-process=image\/auto-orient,1\/format,webp\" alt=\"python\u6570\u636e\u6846\u5982\u4f55\u52a0\u4e00\u5217\" \/><\/p>\n<p><p> <strong>Python \u6570\u636e\u6846\u5982\u4f55\u52a0\u4e00\u5217<\/strong><\/p>\n<\/p>\n<p><p>\u5728Python\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u6765\u64cd\u4f5c\u6570\u636e\u6846\u3002<strong>\u8981\u5728\u6570\u636e\u6846\u4e2d\u6dfb\u52a0\u4e00\u5217\uff0c\u53ef\u4ee5\u4f7f\u7528\u8d4b\u503c\u8bed\u53e5\u3001insert\u65b9\u6cd5\u3001assign\u65b9\u6cd5\u3001join\u65b9\u6cd5<\/strong>\u7b49\u3002\u6bcf\u4e00\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u72ec\u7279\u7684\u5e94\u7528\u573a\u666f\u548c\u4f18\u7f3a\u70b9\uff0c\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5176\u4e2d\u4e00\u79cd\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<p><p><strong>\u8d4b\u503c\u8bed\u53e5<\/strong>\u662f\u6700\u76f4\u63a5\u3001\u6700\u5e38\u7528\u7684\u65b9\u6cd5\u3002\u901a\u8fc7\u76f4\u63a5\u7ed9\u6570\u636e\u6846\u7684\u67d0\u4e00\u5217\u8d4b\u503c\uff0c\u6211\u4eec\u53ef\u4ee5\u65b9\u4fbf\u5730\u6dfb\u52a0\u4e00\u5217\u65b0\u7684\u6570\u636e\u3002\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u6570\u636e\u6846 <code>df<\/code>\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7 <code>df[&#39;new_column&#39;] = values<\/code> \u6765\u6dfb\u52a0\u4e00\u5217 <code>new_column<\/code>\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u8d4b\u503c\u8bed\u53e5<\/h3>\n<\/p>\n<p><p>\u8d4b\u503c\u8bed\u53e5\u662f\u6700\u7b80\u5355\u3001\u76f4\u89c2\u7684\u65b9\u5f0f\u3002\u6211\u4eec\u53ea\u9700\u8981\u5c06\u65b0\u5217\u7684\u540d\u79f0\u4f5c\u4e3a\u952e\uff0c\u8d4b\u4e88\u76f8\u5e94\u7684\u503c\u5373\u53ef\u3002\u4ee5\u4e0b\u662f\u5177\u4f53\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n<ol>\n<li>\u521b\u5efa\u6570\u636e\u6846<\/li>\n<li>\u76f4\u63a5\u8d4b\u503c\u65b0\u5217<\/li>\n<\/ol>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u793a\u4f8b\u6570\u636e\u6846<\/strong><\/h2>\n<p>data = {<\/p>\n<p>    &#39;A&#39;: [1, 2, 3],<\/p>\n<p>    &#39;B&#39;: [4, 5, 6]<\/p>\n<p>}<\/p>\n<p>df = pd.DataFrame(data)<\/p>\n<h2><strong>\u6dfb\u52a0\u65b0\u5217<\/strong><\/h2>\n<p>df[&#39;C&#39;] = [7, 8, 9]<\/p>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u6837\uff0c\u65b0\u7684\u6570\u636e\u6846 <code>df<\/code> \u5c31\u6dfb\u52a0\u4e86\u4e00\u5217 <code>C<\/code>\uff0c\u5176\u503c\u4e3a <code>[7, 8, 9]<\/code>\u3002<\/p>\n<\/p>\n<p><h3>\u4e8c\u3001insert\u65b9\u6cd5<\/h3>\n<\/p>\n<p><p><code>insert<\/code> \u65b9\u6cd5\u5141\u8bb8\u6211\u4eec\u5728\u6307\u5b9a\u4f4d\u7f6e\u63d2\u5165\u65b0\u5217\u3002\u5b83\u7684\u4f7f\u7528\u65b9\u6cd5\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">df.insert(loc=1, column=&#39;D&#39;, value=[10, 11, 12])<\/p>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u4e0a\u9762\u7684\u4f8b\u5b50\u4e2d\uff0c<code>loc=1<\/code> \u8868\u793a\u65b0\u5217 <code>D<\/code> \u5c06\u88ab\u63d2\u5165\u5230\u4f4d\u7f6e 1\uff08\u5373\u7b2c\u4e8c\u5217\uff09\uff0c\u5176\u503c\u4e3a <code>[10, 11, 12]<\/code>\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001assign\u65b9\u6cd5<\/h3>\n<\/p>\n<p><p><code>assign<\/code> \u65b9\u6cd5\u7528\u4e8e\u8fd4\u56de\u4e00\u4e2a\u65b0\u7684\u6570\u636e\u6846\uff0c\u800c\u4e0d\u662f\u5728\u539f\u6570\u636e\u6846\u4e0a\u8fdb\u884c\u4fee\u6539\u3002\u8fd9\u5bf9\u4e8e\u4e0d\u60f3\u6539\u53d8\u539f\u6570\u636e\u6846\u7684\u60c5\u51b5\u975e\u5e38\u6709\u7528\u3002\u4f7f\u7528\u65b9\u6cd5\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">df_new = df.assign(E=[13, 14, 15])<\/p>\n<p>print(df_new)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u56db\u3001join\u65b9\u6cd5<\/h3>\n<\/p>\n<p><p><code>join<\/code> \u65b9\u6cd5\u7528\u4e8e\u5c06\u4e24\u4e2a\u6570\u636e\u6846\u5408\u5e76\u5728\u4e00\u8d77\u3002\u6211\u4eec\u53ef\u4ee5\u521b\u5efa\u4e00\u4e2a\u5355\u72ec\u7684\u6570\u636e\u6846\uff0c\u7136\u540e\u4f7f\u7528 <code>join<\/code> \u65b9\u6cd5\u5c06\u5176\u6dfb\u52a0\u5230\u539f\u6570\u636e\u6846\u4e2d\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">df2 = pd.DataFrame({&#39;F&#39;: [16, 17, 18]})<\/p>\n<p>df = df.join(df2)<\/p>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e94\u3001apply\u65b9\u6cd5<\/h3>\n<\/p>\n<p><p><code>apply<\/code> \u65b9\u6cd5\u901a\u5e38\u7528\u4e8e\u57fa\u4e8e\u73b0\u6709\u5217\u6765\u751f\u6210\u65b0\u5217\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u5e94\u7528\u4e00\u4e2a\u51fd\u6570\u6765\u751f\u6210\u65b0\u5217\u7684\u503c\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">df[&#39;G&#39;] = df.apply(lambda row: row[&#39;A&#39;] + row[&#39;B&#39;], axis=1)<\/p>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u6dfb\u52a0\u4e86\u4e00\u5217 <code>G<\/code>\uff0c\u5176\u503c\u4e3a\u5217 <code>A<\/code> \u548c\u5217 <code>B<\/code> \u7684\u548c\u3002<\/p>\n<\/p>\n<p><h3>\u516d\u3001concat\u65b9\u6cd5<\/h3>\n<\/p>\n<p><p><code>concat<\/code> \u65b9\u6cd5\u7528\u4e8e\u5c06\u4e24\u4e2a\u6216\u591a\u4e2a\u6570\u636e\u6846\u6cbf\u6307\u5b9a\u8f74\uff08\u884c\u6216\u5217\uff09\u8fdb\u884c\u5408\u5e76\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u4f8b\u5b50\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">df2 = pd.DataFrame({<\/p>\n<p>    &#39;H&#39;: [19, 20, 21]<\/p>\n<p>})<\/p>\n<p>df = pd.concat([df, df2], axis=1)<\/p>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e03\u3001\u7ed3\u5408\u5b9e\u9645\u6848\u4f8b<\/h3>\n<\/p>\n<p><p>\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u5305\u542b\u5b66\u751f\u6210\u7ee9\u7684\u6570\u636e\u6846 <code>df<\/code>\uff0c\u6211\u4eec\u60f3\u8981\u6dfb\u52a0\u4e00\u5217 <code>total_score<\/code> \u6765\u8868\u793a\u6bcf\u4e2a\u5b66\u751f\u7684\u603b\u6210\u7ee9\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">data = {<\/p>\n<p>    &#39;student_name&#39;: [&#39;Alice&#39;, &#39;Bob&#39;, &#39;Charlie&#39;],<\/p>\n<p>    &#39;math_score&#39;: [85, 90, 95],<\/p>\n<p>    &#39;english_score&#39;: [88, 92, 94]<\/p>\n<p>}<\/p>\n<p>df = pd.DataFrame(data)<\/p>\n<h2><strong>\u901a\u8fc7 apply \u65b9\u6cd5\u6dfb\u52a0\u603b\u6210\u7ee9\u5217<\/strong><\/h2>\n<p>df[&#39;total_score&#39;] = df.apply(lambda row: row[&#39;math_score&#39;] + row[&#39;english_score&#39;], axis=1)<\/p>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u516b\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u5728Python\u4e2d\uff0c\u4f7f\u7528Pandas\u5e93\u53ef\u4ee5\u65b9\u4fbf\u5730\u64cd\u4f5c\u6570\u636e\u6846\u5e76\u6dfb\u52a0\u65b0\u5217\u3002<strong>\u8d4b\u503c\u8bed\u53e5\u3001insert\u65b9\u6cd5\u3001assign\u65b9\u6cd5\u3001join\u65b9\u6cd5\u3001apply\u65b9\u6cd5\u3001concat\u65b9\u6cd5<\/strong>\u7b49\u90fd\u662f\u5e38\u89c1\u7684\u65b9\u5f0f\u3002\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\uff0c\u53ef\u4ee5\u66f4\u9ad8\u6548\u5730\u5b8c\u6210\u6570\u636e\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><p>\u901a\u8fc7\u672c\u6587\u7684\u8be6\u7ec6\u4ecb\u7ecd\uff0c\u5e0c\u671b\u4f60\u5df2\u7ecf\u638c\u63e1\u4e86\u5728\u6570\u636e\u6846\u4e2d\u6dfb\u52a0\u65b0\u5217\u7684\u5404\u79cd\u65b9\u6cd5\uff0c\u5e76\u80fd\u5728\u5b9e\u9645\u5de5\u4f5c\u4e2d\u7075\u6d3b\u5e94\u7528\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u6570\u636e\u6846\u4e2d\u6dfb\u52a0\u4e00\u5217\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u6765\u5904\u7406\u6570\u636e\u6846\u3002\u8981\u6dfb\u52a0\u4e00\u5217\uff0c\u53ea\u9700\u4f7f\u7528\u65b0\u5217\u540d\u4f5c\u4e3a\u7d22\u5f15\uff0c\u5e76\u8d4b\u4e88\u5b83\u4e00\u4e2a\u503c\u3002\u53ef\u4ee5\u662f\u5e38\u91cf\u3001\u5217\u8868\u6216\u901a\u8fc7\u5176\u4ed6\u5217\u8ba1\u7b97\u5f97\u51fa\u7684\u503c\u3002\u4f8b\u5982\uff1a<code>df[&#39;\u65b0\u5217\u540d&#39;] = \u503c<\/code>\u3002<\/p>\n<p><strong>\u5728\u6dfb\u52a0\u5217\u65f6\u5982\u4f55\u786e\u4fdd\u5217\u7684\u957f\u5ea6\u4e0e\u73b0\u6709\u6570\u636e\u6846\u4e00\u81f4\uff1f<\/strong><br \/>\u5728\u6dfb\u52a0\u65b0\u5217\u65f6\uff0c\u786e\u4fdd\u65b0\u5217\u7684\u6570\u636e\u957f\u5ea6\u4e0e\u6570\u636e\u6846\u7684\u884c\u6570\u76f8\u5339\u914d\u3002\u5982\u679c\u5217\u7684\u957f\u5ea6\u4e0d\u4e00\u81f4\uff0cPandas\u5c06\u5f15\u53d1\u9519\u8bef\u3002\u53ef\u4ee5\u4f7f\u7528<code>len(df)<\/code>\u68c0\u67e5\u6570\u636e\u6846\u7684\u884c\u6570\uff0c\u7136\u540e\u786e\u4fdd\u65b0\u5217\u7684\u6570\u636e\u957f\u5ea6\u4e5f\u662f\u8fd9\u4e2a\u503c\u3002<\/p>\n<p><strong>\u6dfb\u52a0\u65b0\u5217\u65f6\u5982\u4f55\u4f7f\u7528\u73b0\u6709\u5217\u8fdb\u884c\u8ba1\u7b97\uff1f<\/strong><br \/>\u53ef\u4ee5\u901a\u8fc7\u5bf9\u73b0\u6709\u5217\u8fdb\u884c\u8fd0\u7b97\u6765\u521b\u5efa\u65b0\u5217\u3002\u4f8b\u5982\uff0c\u5982\u679c\u4f60\u60f3\u57fa\u4e8e\u4e24\u5217\u7684\u503c\u8ba1\u7b97\u65b0\u5217\uff0c\u53ef\u4ee5\u4f7f\u7528\u7c7b\u4f3c<code>df[&#39;\u65b0\u5217&#39;] = df[&#39;\u52171&#39;] + df[&#39;\u52172&#39;]<\/code>\u7684\u8bed\u6cd5\u3002\u8fd9\u79cd\u65b9\u5f0f\u53ef\u4ee5\u8f7b\u677e\u5730\u521b\u5efa\u57fa\u4e8e\u8ba1\u7b97\u7684\u65b0\u5217\uff0c\u65b9\u4fbf\u6570\u636e\u5206\u6790\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python \u6570\u636e\u6846\u5982\u4f55\u52a0\u4e00\u5217 \u5728Python\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u6765\u64cd\u4f5c\u6570\u636e\u6846\u3002\u8981\u5728\u6570\u636e\u6846\u4e2d\u6dfb\u52a0\u4e00\u5217 [&hellip;]","protected":false},"author":3,"featured_media":1055400,"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\/1055389"}],"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=1055389"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1055389\/revisions"}],"predecessor-version":[{"id":1055402,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1055389\/revisions\/1055402"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1055400"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1055389"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1055389"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1055389"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}