{"id":1141575,"date":"2025-01-08T22:32:19","date_gmt":"2025-01-08T14:32:19","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1141575.html"},"modified":"2025-01-08T22:32:21","modified_gmt":"2025-01-08T14:32:21","slug":"python%e5%a6%82%e4%bd%95%e7%bb%9f%e4%b8%80%e5%88%97%e8%a1%a8%e5%88%97%e7%9a%84%e5%85%83%e7%b4%a0%e7%b1%bb%e5%9e%8b","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1141575.html","title":{"rendered":"python\u5982\u4f55\u7edf\u4e00\u5217\u8868\u5217\u7684\u5143\u7d20\u7c7b\u578b"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25104245\/bc955dcf-7dee-409d-99a4-c5aa8a55755d.webp\" alt=\"python\u5982\u4f55\u7edf\u4e00\u5217\u8868\u5217\u7684\u5143\u7d20\u7c7b\u578b\" \/><\/p>\n<p><p> <strong>\u5728Python\u4e2d\uff0c\u7edf\u4e00\u5217\u8868\u5217\u7684\u5143\u7d20\u7c7b\u578b\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528\u5217\u8868\u89e3\u6790\u3001map\u51fd\u6570\u3001\u4ee5\u53ca\u7c7b\u578b\u8f6c\u6362\u51fd\u6570\u6765\u5b9e\u73b0<\/strong>\u3002\u5176\u4e2d\uff0c\u6700\u5e38\u7528\u7684\u65b9\u6cd5\u662f\u4f7f\u7528\u5217\u8868\u89e3\u6790\uff0c\u56e0\u4e3a\u5b83\u4e0d\u4ec5\u7b80\u6d01\u6613\u8bfb\uff0c\u800c\u4e14\u6548\u7387\u8f83\u9ad8\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u8ba8\u8bba\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u5e76\u901a\u8fc7\u793a\u4f8b\u4ee3\u7801\u8fdb\u884c\u8bf4\u660e\u3002<\/p>\n<\/p>\n<p><h2>\u4e00\u3001\u5217\u8868\u89e3\u6790<\/h2>\n<\/p>\n<p><p>\u5217\u8868\u89e3\u6790\u662f\u4e00\u79cd\u7b80\u6d01\u4e14\u9ad8\u6548\u7684\u65b9\u6cd5\u6765\u521b\u5efa\u548c\u64cd\u4f5c\u5217\u8868\u3002\u901a\u8fc7\u5217\u8868\u89e3\u6790\uff0c\u6211\u4eec\u53ef\u4ee5\u5728\u4e00\u884c\u4ee3\u7801\u4e2d\u5b9e\u73b0\u5c06\u5217\u8868\u4e2d\u7684\u6240\u6709\u5143\u7d20\u8f6c\u6362\u4e3a\u540c\u4e00\u7c7b\u578b\u3002\u5176\u8bed\u6cd5\u4e3a\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">new_list = [expression for item in iterable]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u793a\u4f8b\u4ee3\u7801<\/h3>\n<\/p>\n<p><p>\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u5305\u542b\u4e0d\u540c\u7c7b\u578b\u5143\u7d20\u7684\u5217\u8868\uff0c\u6211\u4eec\u5e0c\u671b\u5c06\u5176\u6240\u6709\u5143\u7d20\u8f6c\u6362\u4e3a\u5b57\u7b26\u4e32\u7c7b\u578b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u539f\u59cb\u5217\u8868<\/p>\n<p>original_list = [1, &#39;2&#39;, 3.0, &#39;4.5&#39;]<\/p>\n<h2><strong>\u7edf\u4e00\u8f6c\u6362\u4e3a\u5b57\u7b26\u4e32\u7c7b\u578b<\/strong><\/h2>\n<p>str_list = [str(element) for element in original_list]<\/p>\n<p>print(str_list)  # \u8f93\u51fa: [&#39;1&#39;, &#39;2&#39;, &#39;3.0&#39;, &#39;4.5&#39;]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><strong>\u5217\u8868\u89e3\u6790\u7684\u4f18\u70b9\u5728\u4e8e\u4ee3\u7801\u7b80\u6d01\u3001\u53ef\u8bfb\u6027\u5f3a\uff0c\u5e76\u4e14\u5728\u5927\u591a\u6570\u60c5\u51b5\u4e0b\u6027\u80fd\u4e5f\u8f83\u4e3a\u4f18\u8d8a<\/strong>\u3002<\/p>\n<\/p>\n<p><h2>\u4e8c\u3001map\u51fd\u6570<\/h2>\n<\/p>\n<p><p><code>map<\/code>\u51fd\u6570\u4e5f\u662f\u4e00\u79cd\u5e38\u7528\u7684\u5217\u8868\u8f6c\u6362\u5de5\u5177\uff0c\u5b83\u53ef\u4ee5\u5c06\u4e00\u4e2a\u51fd\u6570\u5e94\u7528\u5230\u4e00\u4e2a\u53ef\u8fed\u4ee3\u5bf9\u8c61\u7684\u6bcf\u4e2a\u5143\u7d20\u4e0a\uff0c\u5e76\u8fd4\u56de\u4e00\u4e2a\u8fed\u4ee3\u5668\u3002\u5176\u8bed\u6cd5\u4e3a\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">map(function, iterable)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u793a\u4f8b\u4ee3\u7801<\/h3>\n<\/p>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528<code>map<\/code>\u51fd\u6570\u6765\u5b9e\u73b0\u76f8\u540c\u7684\u7c7b\u578b\u8f6c\u6362\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u539f\u59cb\u5217\u8868<\/p>\n<p>original_list = [1, &#39;2&#39;, 3.0, &#39;4.5&#39;]<\/p>\n<h2><strong>\u7edf\u4e00\u8f6c\u6362\u4e3a\u5b57\u7b26\u4e32\u7c7b\u578b<\/strong><\/h2>\n<p>str_list = list(map(str, original_list))<\/p>\n<p>print(str_list)  # \u8f93\u51fa: [&#39;1&#39;, &#39;2&#39;, &#39;3.0&#39;, &#39;4.5&#39;]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><strong>map\u51fd\u6570\u7684\u4f18\u70b9\u5728\u4e8e\u5176\u51fd\u6570\u5f0f\u7f16\u7a0b\u7684\u7279\u6027\uff0c\u4f7f\u5f97\u4ee3\u7801\u8f83\u4e3a\u7b80\u6d01\uff0c\u5e76\u4e14\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\u53ef\u4ee5\u63d0\u9ad8\u6027\u80fd<\/strong>\u3002\u4f46\u76f8\u5bf9\u5217\u8868\u89e3\u6790\u800c\u8a00\uff0cmap\u51fd\u6570\u7684\u53ef\u8bfb\u6027\u7a0d\u5dee\u3002<\/p>\n<\/p>\n<p><h2>\u4e09\u3001for\u5faa\u73af<\/h2>\n<\/p>\n<p><p>\u867d\u7136\u5217\u8868\u89e3\u6790\u548cmap\u51fd\u6570\u5df2\u7ecf\u80fd\u5f88\u597d\u5730\u89e3\u51b3\u95ee\u9898\uff0c\u4f46\u6709\u65f6\u5019\u6211\u4eec\u53ef\u80fd\u9700\u8981\u66f4\u591a\u7684\u63a7\u5236\uff0c\u8fd9\u65f6\u53ef\u4ee5\u4f7f\u7528for\u5faa\u73af\u3002\u901a\u8fc7for\u5faa\u73af\uff0c\u6211\u4eec\u53ef\u4ee5\u5728\u7c7b\u578b\u8f6c\u6362\u8fc7\u7a0b\u4e2d\u6dfb\u52a0\u66f4\u591a\u903b\u8f91\uff0c\u4f8b\u5982\u5f02\u5e38\u5904\u7406\u3002<\/p>\n<\/p>\n<p><h3>\u793a\u4f8b\u4ee3\u7801<\/h3>\n<\/p>\n<p><pre><code class=\"language-python\"># \u539f\u59cb\u5217\u8868<\/p>\n<p>original_list = [1, &#39;2&#39;, 3.0, &#39;4.5&#39;]<\/p>\n<h2><strong>\u7edf\u4e00\u8f6c\u6362\u4e3a\u5b57\u7b26\u4e32\u7c7b\u578b<\/strong><\/h2>\n<p>str_list = []<\/p>\n<p>for element in original_list:<\/p>\n<p>    try:<\/p>\n<p>        str_list.append(str(element))<\/p>\n<p>    except Exception as e:<\/p>\n<p>        print(f&quot;Error converting element {element}: {e}&quot;)<\/p>\n<p>print(str_list)  # \u8f93\u51fa: [&#39;1&#39;, &#39;2&#39;, &#39;3.0&#39;, &#39;4.5&#39;]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><strong>for\u5faa\u73af\u7684\u4f18\u70b9\u5728\u4e8e\u7075\u6d3b\u6027\u9ad8\uff0c\u53ef\u4ee5\u5728\u8f6c\u6362\u8fc7\u7a0b\u4e2d\u6dfb\u52a0\u66f4\u591a\u7684\u903b\u8f91\u548c\u5f02\u5e38\u5904\u7406<\/strong>\u3002<\/p>\n<\/p>\n<p><h2>\u56db\u3001Numpy\u6570\u7ec4<\/h2>\n<\/p>\n<p><p>\u5982\u679c\u5217\u8868\u4e2d\u7684\u5143\u7d20\u4e3b\u8981\u662f\u6570\u503c\u7c7b\u578b\uff0c\u4e14\u9700\u8981\u8fdb\u884c\u5927\u91cf\u7684\u6570\u503c\u8ba1\u7b97\uff0c\u90a3\u4e48\u4f7f\u7528Numpy\u5e93\u53ef\u80fd\u4f1a\u66f4\u4e3a\u9ad8\u6548\u3002Numpy\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u7ec4\u64cd\u4f5c\uff0c\u5e76\u4e14\u53ef\u4ee5\u65b9\u4fbf\u5730\u8f6c\u6362\u6570\u7ec4\u4e2d\u5143\u7d20\u7684\u7c7b\u578b\u3002<\/p>\n<\/p>\n<p><h3>\u793a\u4f8b\u4ee3\u7801<\/h3>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u539f\u59cb\u5217\u8868<\/strong><\/h2>\n<p>original_list = [1, &#39;2&#39;, 3.0, &#39;4.5&#39;]<\/p>\n<h2><strong>\u7edf\u4e00\u8f6c\u6362\u4e3a\u6d6e\u70b9\u6570\u7c7b\u578b<\/strong><\/h2>\n<p>float_array = np.array(original_list, dtype=float)<\/p>\n<p>print(float_array)  # \u8f93\u51fa: [1.  2.  3.  4.5]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><strong>Numpy\u5e93\u7684\u4f18\u70b9\u5728\u4e8e\u5176\u9ad8\u6548\u7684\u6570\u7ec4\u64cd\u4f5c\u548c\u5e7f\u6cdb\u7684\u6570\u503c\u8ba1\u7b97\u529f\u80fd\uff0c\u975e\u5e38\u9002\u5408\u9700\u8981\u8fdb\u884c\u5927\u91cf\u6570\u503c\u8ba1\u7b97\u7684\u573a\u666f<\/strong>\u3002<\/p>\n<\/p>\n<p><h2>\u4e94\u3001Pandas DataFrame<\/h2>\n<\/p>\n<p><p>\u5728\u5904\u7406\u6570\u636e\u65f6\uff0cPandas\u5e93\u4e5f\u975e\u5e38\u5e38\u7528\u3002\u6211\u4eec\u53ef\u4ee5\u5c06\u5217\u8868\u8f6c\u6362\u4e3aPandas DataFrame\uff0c\u7136\u540e\u4f7f\u7528DataFrame\u7684\u5185\u7f6e\u51fd\u6570\u6765\u7edf\u4e00\u5217\u7684\u7c7b\u578b\u3002<\/p>\n<\/p>\n<p><h3>\u793a\u4f8b\u4ee3\u7801<\/h3>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u539f\u59cb\u5217\u8868<\/strong><\/h2>\n<p>original_list = [1, &#39;2&#39;, 3.0, &#39;4.5&#39;]<\/p>\n<h2><strong>\u521b\u5efaDataFrame<\/strong><\/h2>\n<p>df = pd.DataFrame(original_list, columns=[&#39;values&#39;])<\/p>\n<h2><strong>\u7edf\u4e00\u8f6c\u6362\u4e3a\u5b57\u7b26\u4e32\u7c7b\u578b<\/strong><\/h2>\n<p>df[&#39;values&#39;] = df[&#39;values&#39;].astype(str)<\/p>\n<p>print(df)  # \u8f93\u51fa: DataFrame\uff0c\u5176\u4e2d\u6240\u6709\u5143\u7d20\u5747\u4e3a\u5b57\u7b26\u4e32\u7c7b\u578b<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><strong>Pandas\u5e93\u7684\u4f18\u70b9\u5728\u4e8e\u5176\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u80fd\u529b\u548c\u4e30\u5bcc\u7684\u5185\u7f6e\u51fd\u6570\uff0c\u7279\u522b\u9002\u5408\u6570\u636e\u5206\u6790\u548c\u5904\u7406\u4efb\u52a1<\/strong>\u3002<\/p>\n<\/p>\n<p><h2>\u7ed3\u8bba<\/h2>\n<\/p>\n<p><p>\u5728Python\u4e2d\uff0c\u7edf\u4e00\u5217\u8868\u5217\u7684\u5143\u7d20\u7c7b\u578b\u6709\u591a\u79cd\u65b9\u6cd5\u53ef\u4f9b\u9009\u62e9\uff0c\u5176\u4e2d\u5217\u8868\u89e3\u6790\u3001map\u51fd\u6570\u3001for\u5faa\u73af\u3001Numpy\u6570\u7ec4\u548cPandas DataFrame\u662f\u6700\u5e38\u7528\u7684\u51e0\u79cd\u3002<strong>\u5217\u8868\u89e3\u6790\u548cmap\u51fd\u6570\u9002\u7528\u4e8e\u5927\u591a\u6570\u7b80\u5355\u7684\u7c7b\u578b\u8f6c\u6362\u4efb\u52a1\uff0cfor\u5faa\u73af\u9002\u7528\u4e8e\u9700\u8981\u66f4\u591a\u63a7\u5236\u7684\u60c5\u51b5\uff0cNumpy\u548cPandas\u5e93\u5219\u9002\u7528\u4e8e\u6570\u636e\u5904\u7406\u548c\u6570\u503c\u8ba1\u7b97\u4efb\u52a1<\/strong>\u3002\u6839\u636e\u5177\u4f53\u7684\u4f7f\u7528\u573a\u666f\u548c\u9700\u6c42\uff0c\u9009\u62e9\u6700\u9002\u5408\u7684\u65b9\u6cd5\u53ef\u4ee5\u63d0\u9ad8\u4ee3\u7801\u7684\u6548\u7387\u548c\u53ef\u8bfb\u6027\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u5c06\u5217\u8868\u4e2d\u7684\u6240\u6709\u5143\u7d20\u8f6c\u6362\u4e3a\u76f8\u540c\u7684\u6570\u636e\u7c7b\u578b\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f\u7ed3\u5408\u5185\u7f6e\u7684\u7c7b\u578b\u8f6c\u6362\u51fd\u6570\u6765\u7edf\u4e00\u5217\u8868\u4e2d\u5143\u7d20\u7684\u7c7b\u578b\u3002\u4f8b\u5982\uff0c\u5982\u679c\u5e0c\u671b\u5c06\u5217\u8868\u4e2d\u7684\u6240\u6709\u5143\u7d20\u8f6c\u6362\u4e3a\u5b57\u7b26\u4e32\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<code>my_list = [str(item) for item in my_list]<\/code>\u3002\u8fd9\u6837\uff0c\u5217\u8868\u4e2d\u7684\u6bcf\u4e2a\u5143\u7d20\u90fd\u4f1a\u88ab\u8f6c\u6362\u4e3a\u5b57\u7b26\u4e32\u3002<\/p>\n<p><strong>\u5217\u8868\u4e2d\u5143\u7d20\u7c7b\u578b\u4e0d\u4e00\u81f4\u4f1a\u5f71\u54cd\u54ea\u4e9b\u64cd\u4f5c\uff1f<\/strong><br \/>\u5217\u8868\u4e2d\u5143\u7d20\u7c7b\u578b\u4e0d\u4e00\u81f4\u53ef\u80fd\u4f1a\u5bfc\u81f4\u4e00\u4e9b\u5e38\u89c1\u64cd\u4f5c\u51fa\u73b0\u9519\u8bef\uff0c\u4f8b\u5982\u5728\u8fdb\u884c\u6570\u5b66\u8fd0\u7b97\u65f6\u3002\u5982\u679c\u5217\u8868\u5305\u542b\u6574\u6570\u548c\u5b57\u7b26\u4e32\uff0c\u5c1d\u8bd5\u8fdb\u884c\u52a0\u6cd5\u6216\u5176\u4ed6\u6570\u5b66\u64cd\u4f5c\u65f6\u4f1a\u629b\u51faTypeError\u3002\u56e0\u6b64\uff0c\u786e\u4fdd\u5143\u7d20\u7c7b\u578b\u7edf\u4e00\u53ef\u4ee5\u63d0\u9ad8\u4ee3\u7801\u7684\u53ef\u9760\u6027\u548c\u53ef\u8bfb\u6027\u3002<\/p>\n<p><strong>\u5728\u5904\u7406\u5927\u578b\u6570\u636e\u65f6\uff0c\u5982\u4f55\u6709\u6548\u5730\u7edf\u4e00\u5217\u8868\u5143\u7d20\u7684\u7c7b\u578b\uff1f<\/strong><br \/>\u5728\u5904\u7406\u5927\u578b\u6570\u636e\u65f6\uff0c\u53ef\u4ee5\u8003\u8651\u4f7f\u7528Pandas\u5e93\u3002Pandas\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u80fd\u529b\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u5c06Series\u6216DataFrame\u4e2d\u7684\u5143\u7d20\u7c7b\u578b\u8f6c\u6362\u4e3a\u7edf\u4e00\u7684\u7c7b\u578b\u3002\u4f8b\u5982\uff0c\u4f7f\u7528<code>pd.Series(my_list).astype(&#39;desired_type&#39;)<\/code>\uff0c\u53ef\u4ee5\u5feb\u901f\u5c06\u6240\u6709\u5143\u7d20\u8f6c\u6362\u4e3a\u6307\u5b9a\u7c7b\u578b\uff0c\u540c\u65f6\u4fdd\u6301\u64cd\u4f5c\u7684\u9ad8\u6548\u6027\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u7edf\u4e00\u5217\u8868\u5217\u7684\u5143\u7d20\u7c7b\u578b\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528\u5217\u8868\u89e3\u6790\u3001map\u51fd\u6570\u3001\u4ee5\u53ca\u7c7b\u578b\u8f6c\u6362\u51fd\u6570\u6765\u5b9e\u73b0\u3002\u5176\u4e2d\uff0c\u6700\u5e38\u7528\u7684 [&hellip;]","protected":false},"author":3,"featured_media":1141584,"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\/1141575"}],"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=1141575"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1141575\/revisions"}],"predecessor-version":[{"id":1141585,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1141575\/revisions\/1141585"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1141584"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1141575"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1141575"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1141575"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}