{"id":969752,"date":"2024-12-27T05:19:49","date_gmt":"2024-12-26T21:19:49","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/969752.html"},"modified":"2024-12-27T05:19:51","modified_gmt":"2024-12-26T21:19:51","slug":"python%e5%a6%82%e4%bd%95%e6%98%be%e7%a4%ba%e5%85%a8%e6%95%b0%e7%bb%84","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/969752.html","title":{"rendered":"python\u5982\u4f55\u663e\u793a\u5168\u6570\u7ec4"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/24183901\/9e3c29e5-0c77-4657-ba02-dbc6b1692755.webp\" alt=\"python\u5982\u4f55\u663e\u793a\u5168\u6570\u7ec4\" \/><\/p>\n<p><p> \u5728Python\u4e2d\uff0c<strong>\u53ef\u4ee5\u901a\u8fc7\u8c03\u6574\u6253\u5370\u9009\u9879\u4ee5\u663e\u793a\u5b8c\u6574\u7684\u6570\u7ec4\u3001\u4f7f\u7528\u5e93\u51fd\u6570\u5c06\u6570\u7ec4\u8f6c\u6362\u4e3a\u5b57\u7b26\u4e32\u683c\u5f0f\u3001\u6216\u8005\u4f7f\u7528\u81ea\u5b9a\u4e49\u51fd\u6570\u6765\u9010\u884c\u663e\u793a\u6570\u7ec4\u7684\u6bcf\u4e2a\u5143\u7d20<\/strong>\u3002\u4ee5\u4e0b\u662f\u5176\u4e2d\u4e00\u79cd\u65b9\u6cd5\u7684\u8be6\u7ec6\u63cf\u8ff0\uff1a\u4f7f\u7528NumPy\u5e93\u4e2d\u7684<code>set_printoptions<\/code>\u51fd\u6570\u8c03\u6574\u6570\u7ec4\u6253\u5370\u9009\u9879\u3002NumPy\u662fPython\u4e2d\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u7684\u6838\u5fc3\u5e93\u4e4b\u4e00\uff0c\u5b83\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u7ec4\u5bf9\u8c61\u548c\u591a\u79cd\u5de5\u5177\u6765\u64cd\u4f5c\u8fd9\u4e9b\u6570\u7ec4\u3002<\/p>\n<\/p>\n<p><p>\u901a\u8fc7<code>numpy.set_printoptions(threshold=numpy.inf)<\/code>\uff0c\u4f60\u53ef\u4ee5\u8bbe\u7f6e\u6253\u5370\u9009\u9879\u4ee5\u663e\u793a\u6570\u7ec4\u7684\u6240\u6709\u5143\u7d20\uff0c\u800c\u4e0d\u662f\u4ee5\u7701\u7565\u53f7\u8868\u793a\u3002\u8fd9\u79cd\u65b9\u6cd5\u975e\u5e38\u9002\u7528\u4e8e\u9700\u8981\u68c0\u67e5\u5927\u6570\u7ec4\u7684\u573a\u5408\u3002\u5177\u4f53\u6765\u8bf4\uff0c<code>threshold<\/code>\u53c2\u6570\u51b3\u5b9a\u4e86\u8d85\u8fc7\u591a\u5c11\u5143\u7d20\u540e\u4f7f\u7528\u7701\u7565\u53f7\uff0c\u8bbe\u7f6e\u4e3a<code>numpy.inf<\/code>\u53ef\u4ee5\u907f\u514d\u7701\u7565\u53f7\u7684\u51fa\u73b0\u3002<\/p>\n<\/p>\n<hr>\n<p><h2>\u4e00\u3001\u4f7f\u7528NUMPY\u5e93\u663e\u793a\u5168\u6570\u7ec4<\/h2>\n<\/p>\n<p><h3>1. \u57fa\u7840\u8bbe\u7f6e\u548c\u4f7f\u7528<\/h3>\n<\/p>\n<p><p>NumPy\u5e93\u662fPython\u4e2d\u5904\u7406\u6570\u7ec4\u7684\u6700\u5f3a\u5927\u5de5\u5177\u4e4b\u4e00\uff0c\u5b83\u4e0d\u4ec5\u53ef\u4ee5\u5904\u7406\u591a\u7ef4\u6570\u7ec4\uff0c\u8fd8\u63d0\u4f9b\u4e86\u591a\u79cd\u51fd\u6570\u548c\u65b9\u6cd5\u6765\u64cd\u4f5c\u8fd9\u4e9b\u6570\u7ec4\u3002\u4e3a\u4e86\u663e\u793a\u5b8c\u6574\u7684\u6570\u7ec4\u5185\u5bb9\uff0c\u5c24\u5176\u662f\u5bf9\u4e8e\u5927\u578b\u6570\u7ec4\uff0c<code>numpy.set_printoptions<\/code>\u662f\u4e00\u4e2a\u975e\u5e38\u6709\u7528\u7684\u51fd\u6570\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u5927\u578b\u6570\u7ec4<\/strong><\/h2>\n<p>large_array = np.arange(10000)<\/p>\n<h2><strong>\u8bbe\u7f6e\u6253\u5370\u9009\u9879\u4ee5\u663e\u793a\u5b8c\u6574\u7684\u6570\u7ec4<\/strong><\/h2>\n<p>np.set_printoptions(threshold=np.inf)<\/p>\n<h2><strong>\u6253\u5370\u6570\u7ec4<\/strong><\/h2>\n<p>print(large_array)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u6574\u4e2a\u6570\u7ec4\u7684\u5185\u5bb9\u5c06\u4f1a\u88ab\u5b8c\u6574\u663e\u793a\uff0c\u800c\u4e0d\u662f\u7528\u7701\u7565\u53f7\u6765\u4ee3\u66ff\u5927\u90e8\u5206\u5185\u5bb9\u3002\u8fd9\u5728\u8c03\u8bd5\u548c\u6570\u636e\u5206\u6790\u65f6\u975e\u5e38\u6709\u7528\u3002<\/p>\n<\/p>\n<p><h3>2. \u5176\u4ed6\u6709\u7528\u7684\u6253\u5370\u9009\u9879<\/h3>\n<\/p>\n<p><p>\u9664\u4e86<code>threshold<\/code>\u4e4b\u5916\uff0c<code>numpy.set_printoptions<\/code>\u8fd8\u63d0\u4f9b\u4e86\u5176\u4ed6\u6709\u7528\u7684\u53c2\u6570\uff0c\u4f8b\u5982\uff1a<\/p>\n<\/p>\n<ul>\n<li><code>precision<\/code>\uff1a\u63a7\u5236\u6d6e\u70b9\u6570\u7684\u663e\u793a\u7cbe\u5ea6\u3002<\/li>\n<li><code>suppress<\/code>\uff1a\u5728\u663e\u793a\u6d6e\u70b9\u6570\u65f6\u6291\u5236\u79d1\u5b66\u8ba1\u6570\u6cd5\u3002<\/li>\n<li><code>linewidth<\/code>\uff1a\u6bcf\u884c\u663e\u793a\u7684\u6700\u5927\u5b57\u7b26\u6570\u3002<\/li>\n<\/ul>\n<p><p>\u901a\u8fc7\u8fd9\u4e9b\u53c2\u6570\uff0c\u6211\u4eec\u53ef\u4ee5\u8fdb\u4e00\u6b65\u81ea\u5b9a\u4e49\u6570\u7ec4\u7684\u663e\u793a\u683c\u5f0f\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">np.set_printoptions(precision=3, suppress=True, linewidth=100)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u79cd\u7075\u6d3b\u6027\u4f7f\u5f97NumPy\u5728\u5904\u7406\u548c\u5c55\u793a\u6570\u636e\u65f6\u975e\u5e38\u5f3a\u5927\u3002<\/p>\n<\/p>\n<hr>\n<p><h2>\u4e8c\u3001\u4f7f\u7528PANDAS\u5e93\u663e\u793a\u5168\u6570\u7ec4<\/h2>\n<\/p>\n<p><h3>1. \u5c06\u6570\u7ec4\u8f6c\u6362\u4e3aDataFrame<\/h3>\n<\/p>\n<p><p>Pandas\u662f\u53e6\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u5e93\uff0c\u7279\u522b\u9002\u5408\u5904\u7406\u8868\u683c\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u5c06NumPy\u6570\u7ec4\u8f6c\u6362\u4e3aPandas\u7684DataFrame\uff0c\u4ee5\u4fbf\u66f4\u597d\u5730\u663e\u793a\u548c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u5c06NumPy\u6570\u7ec4\u8f6c\u6362\u4e3aDataFrame<\/strong><\/h2>\n<p>df = pd.DataFrame(large_array)<\/p>\n<h2><strong>\u663e\u793aDataFrame<\/strong><\/h2>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>Pandas\u7684DataFrame\u4e0d\u4ec5\u53ef\u4ee5\u663e\u793a\u5b8c\u6574\u7684\u6570\u636e\uff0c\u8fd8\u53ef\u4ee5\u8fdb\u884c\u66f4\u590d\u6742\u7684\u6570\u636e\u64cd\u4f5c\u548c\u5206\u6790\u3002<\/p>\n<\/p>\n<p><h3>2. \u914d\u7f6ePandas\u7684\u663e\u793a\u9009\u9879<\/h3>\n<\/p>\n<p><p>\u4e0eNumPy\u7c7b\u4f3c\uff0cPandas\u4e5f\u63d0\u4f9b\u4e86\u591a\u79cd\u9009\u9879\u6765\u63a7\u5236\u6570\u636e\u7684\u663e\u793a\u3002\u901a\u8fc7<code>pd.set_option<\/code>\uff0c\u6211\u4eec\u53ef\u4ee5\u8c03\u6574\u884c\u548c\u5217\u7684\u663e\u793a\u6570\u91cf\u3001\u6d6e\u70b9\u6570\u7cbe\u5ea6\u7b49\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">pd.set_option(&#39;display.max_rows&#39;, None)<\/p>\n<p>pd.set_option(&#39;display.max_columns&#39;, None)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u79cd\u65b9\u6cd5\u540c\u6837\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u5728\u5904\u7406\u5927\u91cf\u6570\u636e\u65f6\uff0c\u5b8c\u6574\u5730\u67e5\u770b\u548c\u5206\u6790\u6570\u636e\u3002<\/p>\n<\/p>\n<hr>\n<p><h2>\u4e09\u3001\u4f7f\u7528\u81ea\u5b9a\u4e49\u51fd\u6570\u663e\u793a\u5168\u6570\u7ec4<\/h2>\n<\/p>\n<p><h3>1. \u521b\u5efa\u81ea\u5b9a\u4e49\u6253\u5370\u51fd\u6570<\/h3>\n<\/p>\n<p><p>\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u53ef\u80fd\u9700\u8981\u5bf9\u6570\u7ec4\u8fdb\u884c\u7279\u6b8a\u7684\u683c\u5f0f\u5316\u5904\u7406\u3002\u8fd9\u65f6\u53ef\u4ee5\u7f16\u5199\u4e00\u4e2a\u81ea\u5b9a\u4e49\u51fd\u6570\u6765\u9010\u884c\u6253\u5370\u6570\u7ec4\u7684\u6bcf\u4e00\u4e2a\u5143\u7d20\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def print_full_array(arr):<\/p>\n<p>    for element in arr:<\/p>\n<p>        print(element)<\/p>\n<h2><strong>\u4f7f\u7528\u81ea\u5b9a\u4e49\u51fd\u6570\u6253\u5370\u6570\u7ec4<\/strong><\/h2>\n<p>print_full_array(large_array)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u79cd\u65b9\u6cd5\u7684\u7075\u6d3b\u6027\u5728\u4e8e\uff0c\u6211\u4eec\u53ef\u4ee5\u6839\u636e\u9700\u8981\u6dfb\u52a0\u4efb\u4f55\u81ea\u5b9a\u4e49\u7684\u683c\u5f0f\u6216\u903b\u8f91\u3002<\/p>\n<\/p>\n<p><h3>2. \u5904\u7406\u591a\u7ef4\u6570\u7ec4<\/h3>\n<\/p>\n<p><p>\u5bf9\u4e8e\u591a\u7ef4\u6570\u7ec4\uff0c\u81ea\u5b9a\u4e49\u51fd\u6570\u53ef\u4ee5\u88ab\u6269\u5c55\u4ee5\u9012\u5f52\u7684\u65b9\u5f0f\u5904\u7406\u6bcf\u4e00\u4e2a\u7ef4\u5ea6\uff0c\u786e\u4fdd\u5b8c\u6574\u663e\u793a\u6570\u7ec4\u7684\u6bcf\u4e00\u4e2a\u5143\u7d20\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def print_full_array_recursive(arr):<\/p>\n<p>    if arr.ndim == 1:<\/p>\n<p>        for element in arr:<\/p>\n<p>            print(element)<\/p>\n<p>    else:<\/p>\n<p>        for sub_array in arr:<\/p>\n<p>            print_full_array_recursive(sub_array)<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u591a\u7ef4\u6570\u7ec4<\/strong><\/h2>\n<p>multi_array = np.arange(27).reshape(3, 3, 3)<\/p>\n<h2><strong>\u4f7f\u7528\u81ea\u5b9a\u4e49\u51fd\u6570\u6253\u5370\u591a\u7ef4\u6570\u7ec4<\/strong><\/h2>\n<p>print_full_array_recursive(multi_array)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u79cd\u9012\u5f52\u65b9\u6cd5\u53ef\u4ee5\u5904\u7406\u4efb\u610f\u7ef4\u5ea6\u7684\u6570\u7ec4\uff0c\u786e\u4fdd\u6570\u636e\u7684\u5b8c\u6574\u6027\u3002<\/p>\n<\/p>\n<hr>\n<p><h2>\u56db\u3001\u603b\u7ed3\u4e0e\u5e94\u7528\u573a\u666f<\/h2>\n<\/p>\n<p><h3>1. \u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5<\/h3>\n<\/p>\n<p><p>\u663e\u793a\u5b8c\u6574\u6570\u7ec4\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u9009\u62e9\u54ea\u4e00\u79cd\u53d6\u51b3\u4e8e\u5177\u4f53\u7684\u5e94\u7528\u573a\u666f\u548c\u9700\u6c42\u3002\u4f8b\u5982\uff0c\u4f7f\u7528NumPy\u7684<code>set_printoptions<\/code>\u9002\u5408\u9700\u8981\u5feb\u901f\u67e5\u770b\u548c\u8c03\u8bd5\u5927\u6570\u7ec4\u7684\u573a\u5408\uff0c\u800cPandas\u5219\u66f4\u9002\u5408\u5904\u7406\u7ed3\u6784\u5316\u7684\u8868\u683c\u6570\u636e\u3002<\/p>\n<\/p>\n<p><h3>2. \u5728\u6570\u636e\u5206\u6790\u4e2d\u7684\u5e94\u7528<\/h3>\n<\/p>\n<p><p>\u5728\u6570\u636e\u5206\u6790\u4e2d\uff0c\u67e5\u770b\u5b8c\u6574\u7684\u6570\u636e\u96c6\u5bf9\u4e8e\u7406\u89e3\u6570\u636e\u7684\u7ed3\u6784\u548c\u5185\u5bb9\u81f3\u5173\u91cd\u8981\u3002\u65e0\u8bba\u662f\u4f7f\u7528NumPy\u8fd8\u662fPandas\uff0c\u6211\u4eec\u90fd\u53ef\u4ee5\u6839\u636e\u9700\u8981\u8c03\u6574\u6570\u636e\u7684\u663e\u793a\u65b9\u5f0f\uff0c\u4ee5\u4fbf\u66f4\u597d\u5730\u8fdb\u884c\u5206\u6790\u548c\u51b3\u7b56\u3002<\/p>\n<\/p>\n<p><h3>3. \u5bf9\u4e8e\u5927\u6570\u636e\u7684\u5904\u7406<\/h3>\n<\/p>\n<p><p>\u5728\u5927\u6570\u636e\u5904\u7406\u4e2d\uff0c\u663e\u793a\u5b8c\u6574\u6570\u636e\u96c6\u53ef\u80fd\u4f1a\u975e\u5e38\u8017\u65f6\u4e14\u8d44\u6e90\u5bc6\u96c6\u3002\u56e0\u6b64\uff0c\u5728\u73b0\u5b9e\u5e94\u7528\u4e2d\uff0c\u6211\u4eec\u901a\u5e38\u9700\u8981\u7ed3\u5408\u6570\u636e\u91c7\u6837\u3001\u5206\u5757\u5904\u7406\u7b49\u6280\u672f\uff0c\u4ee5\u9ad8\u6548\u5730\u67e5\u770b\u548c\u5206\u6790\u6570\u636e\u3002<\/p>\n<\/p>\n<p><p>\u901a\u8fc7\u7406\u89e3\u548c\u5e94\u7528\u4e0a\u8ff0\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u5728Python\u4e2d\u7075\u6d3b\u9ad8\u6548\u5730\u5904\u7406\u548c\u663e\u793a\u5404\u79cd\u7c7b\u578b\u7684\u6570\u7ec4\uff0c\u63d0\u5347\u6570\u636e\u5206\u6790\u548c\u79d1\u5b66\u8ba1\u7b97\u7684\u6548\u7387\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u6253\u5370\u51fa\u5b8c\u6574\u7684\u6570\u7ec4\u5185\u5bb9\u800c\u4e0d\u88ab\u622a\u65ad\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528<code>numpy<\/code>\u5e93\u7684<code>set_printoptions<\/code>\u51fd\u6570\u6765\u8bbe\u7f6e\u6253\u5370\u9009\u9879\uff0c\u4ece\u800c\u663e\u793a\u5b8c\u6574\u7684\u6570\u7ec4\u3002\u901a\u8fc7\u8c03\u6574<code>threshold<\/code>\u53c2\u6570\uff0c\u53ef\u4ee5\u6539\u53d8\u5728\u6253\u5370\u65f6\u622a\u65ad\u7684\u9608\u503c\u3002\u4f8b\u5982\uff0c\u8bbe\u7f6e<code>numpy.set_printoptions(threshold=np.inf)<\/code>\u53ef\u4ee5\u8ba9\u4f60\u770b\u5230\u5b8c\u6574\u7684\u6570\u7ec4\u5185\u5bb9\u3002<\/p>\n<p><strong>\u5728Python\u4e2d\u5982\u4f55\u67e5\u770b\u6570\u7ec4\u7684\u7ef4\u5ea6\u548c\u5f62\u72b6\uff1f<\/strong><br 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