{"id":1088765,"date":"2025-01-08T13:47:20","date_gmt":"2025-01-08T05:47:20","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1088765.html"},"modified":"2025-01-08T13:47:23","modified_gmt":"2025-01-08T05:47:23","slug":"%e5%a6%82%e4%bd%95%e8%ae%be%e7%bd%aepython%e4%b8%ad%e6%95%b0%e6%8d%ae%e7%9a%84%e5%9f%9f%e5%ae%bd-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1088765.html","title":{"rendered":"\u5982\u4f55\u8bbe\u7f6epython\u4e2d\u6570\u636e\u7684\u57df\u5bbd"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/24201042\/61ebb751-6d9a-4308-a235-177e5895ae30.webp\" alt=\"\u5982\u4f55\u8bbe\u7f6epython\u4e2d\u6570\u636e\u7684\u57df\u5bbd\" \/><\/p>\n<p><p> <strong>\u5728Python\u4e2d\u8bbe\u7f6e\u6570\u636e\u7684\u57df\u5bbd\uff0c\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528\u5b57\u7b26\u4e32\u7684\u683c\u5f0f\u5316\u65b9\u6cd5\u3001\u4f7f\u7528<code>pandas<\/code>\u5e93\u4e2d\u7684<code>pd.options.display<\/code>\u8bbe\u7f6e\u3001\u6216\u8005\u4f7f\u7528<code>numpy<\/code>\u5e93\u4e2d\u7684<code>set_printoptions<\/code>\u65b9\u6cd5\u6765\u5b9e\u73b0<\/strong>\u3002\u5176\u4e2d\uff0c\u4f7f\u7528<code>pandas<\/code>\u5e93\u4e2d\u7684<code>pd.options.display<\/code>\u8bbe\u7f6e\u57df\u5bbd\u66f4\u4e3a\u5e38\u89c1\uff0c\u56e0\u4e3a\u5b83\u80fd\u591f\u5e2e\u52a9\u6211\u4eec\u5728\u5904\u7406\u548c\u5c55\u793a\u6570\u636e\u65f6\u66f4\u52a0\u7075\u6d3b\u548c\u65b9\u4fbf\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u901a\u8fc7\u8fd9\u51e0\u79cd\u65b9\u6cd5\u8bbe\u7f6e\u6570\u636e\u7684\u57df\u5bbd\u3002<\/p>\n<\/p>\n<p><h3>\u4f7f\u7528\u5b57\u7b26\u4e32\u683c\u5f0f\u5316\u65b9\u6cd5<\/h3>\n<\/p>\n<p><p>\u5b57\u7b26\u4e32\u683c\u5f0f\u5316\u65b9\u6cd5\u53ef\u4ee5\u7528\u6765\u63a7\u5236\u8f93\u51fa\u6570\u636e\u7684\u57df\u5bbd\u3002Python\u63d0\u4f9b\u4e86\u591a\u79cd\u5b57\u7b26\u4e32\u683c\u5f0f\u5316\u7684\u65b9\u6cd5\uff0c\u5305\u62ec\u65e7\u5f0f\u7684\u767e\u5206\u53f7 <code>%<\/code> \u683c\u5f0f\u5316\u3001\u65b0\u5f0f\u7684 <code>str.format()<\/code> \u65b9\u6cd5\u4ee5\u53ca\u6700\u65b0\u7684f-string\uff08\u683c\u5f0f\u5316\u5b57\u7b26\u4e32\u5b57\u9762\u91cf\uff09\u3002\u4e0b\u9762\u662f\u8fd9\u51e0\u79cd\u65b9\u6cd5\u7684\u8be6\u7ec6\u4f7f\u7528\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u65e7\u5f0f\u7684\u767e\u5206\u53f7 % \u683c\u5f0f\u5316<\/p>\n<p>num = 123.456<\/p>\n<p>print(&#39;%10.2f&#39; % num)  # \u8f93\u51fa\uff1a    123.46<\/p>\n<h2><strong>\u65b0\u5f0f\u7684 str.format() \u65b9\u6cd5<\/strong><\/h2>\n<p>print(&#39;{:10.2f}&#39;.format(num))  # \u8f93\u51fa\uff1a    123.46<\/p>\n<h2><strong>\u6700\u65b0\u7684 f-string\uff08\u683c\u5f0f\u5316\u5b57\u7b26\u4e32\u5b57\u9762\u91cf\uff09<\/strong><\/h2>\n<p>print(f&#39;{num:10.2f}&#39;)  # \u8f93\u51fa\uff1a    123.46<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4f7f\u7528<code>pandas<\/code>\u5e93\u8bbe\u7f6e\u663e\u793a\u9009\u9879<\/h3>\n<\/p>\n<p><p><code>pandas<\/code>\u5e93\u662fPython\u4e2d\u975e\u5e38\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u5e93\uff0c\u5177\u6709\u4e30\u5bcc\u7684\u6570\u636e\u64cd\u4f5c\u529f\u80fd\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u8c03\u6574<code>pd.options.display<\/code>\u4e2d\u7684\u8bbe\u7f6e\u6765\u63a7\u5236\u6570\u636e\u5c55\u793a\u7684\u57df\u5bbd\u3002\u5177\u4f53\u7684\u8bbe\u7f6e\u65b9\u6cd5\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u793a\u4f8bDataFrame<\/strong><\/h2>\n<p>data = {&#39;A&#39;: [1, 2, 3], &#39;B&#39;: [123.456, 78.90, 12.3456]}<\/p>\n<p>df = pd.DataFrame(data)<\/p>\n<h2><strong>\u8bbe\u7f6e\u5217\u5bbd\u4e3a20<\/strong><\/h2>\n<p>pd.options.display.max_colwidth = 20<\/p>\n<h2><strong>\u663e\u793aDataFrame<\/strong><\/h2>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4f7f\u7528<code>numpy<\/code>\u5e93\u8bbe\u7f6e\u663e\u793a\u9009\u9879<\/h3>\n<\/p>\n<p><p><code>numpy<\/code>\u5e93\u662fPython\u4e2d\u6700\u57fa\u7840\u7684\u79d1\u5b66\u8ba1\u7b97\u5e93\u4e4b\u4e00\uff0c\u5e7f\u6cdb\u5e94\u7528\u4e8e\u6570\u636e\u5904\u7406\u548c\u79d1\u5b66\u8ba1\u7b97\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7<code>numpy.set_printoptions<\/code>\u65b9\u6cd5\u6765\u8bbe\u7f6e\u8f93\u51fa\u6570\u636e\u7684\u57df\u5bbd\u3002\u5177\u4f53\u7684\u8bbe\u7f6e\u65b9\u6cd5\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u793a\u4f8b\u6570\u7ec4<\/strong><\/h2>\n<p>arr = np.array([123.456, 78.90, 12.3456])<\/p>\n<h2><strong>\u8bbe\u7f6e\u6253\u5370\u9009\u9879<\/strong><\/h2>\n<p>np.set_printoptions(formatter={&#39;float&#39;: &#39;{:10.2f}&#39;.format})<\/p>\n<h2><strong>\u663e\u793a\u6570\u7ec4<\/strong><\/h2>\n<p>print(arr)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7\u4ee5\u4e0a\u51e0\u79cd\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u7075\u6d3b\u5730\u63a7\u5236Python\u4e2d\u6570\u636e\u7684\u57df\u5bbd\uff0c\u4ee5\u4fbf\u66f4\u597d\u5730\u5c55\u793a\u6570\u636e\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u63a2\u8ba8\u6bcf\u79cd\u65b9\u6cd5\u7684\u5177\u4f53\u5b9e\u73b0\u548c\u6ce8\u610f\u4e8b\u9879\u3002<\/p>\n<\/p>\n<p><h2>\u4e00\u3001\u4f7f\u7528\u5b57\u7b26\u4e32\u683c\u5f0f\u5316\u65b9\u6cd5<\/h2>\n<\/p>\n<p><p>\u5b57\u7b26\u4e32\u683c\u5f0f\u5316\u65b9\u6cd5\u662f\u63a7\u5236\u8f93\u51fa\u6570\u636e\u57df\u5bbd\u7684\u57fa\u7840\u65b9\u6cd5\uff0c\u9002\u7528\u4e8e\u5404\u79cd\u7b80\u5355\u7684\u5b57\u7b26\u4e32\u5904\u7406\u573a\u666f\u3002<\/p>\n<\/p>\n<p><h3>1\u3001\u65e7\u5f0f\u7684\u767e\u5206\u53f7 % \u683c\u5f0f\u5316<\/h3>\n<\/p>\n<p><p>\u65e7\u5f0f\u7684\u767e\u5206\u53f7 <code>%<\/code> \u683c\u5f0f\u5316\u662fPython\u6700\u65e9\u63d0\u4f9b\u7684\u5b57\u7b26\u4e32\u683c\u5f0f\u5316\u65b9\u6cd5\u3002\u5176\u57fa\u672c\u8bed\u6cd5\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">&#39;%[\u5bbd\u5ea6][.\u7cbe\u5ea6]\u7c7b\u578b&#39; % \u503c<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u6765\u63a7\u5236\u8f93\u51fa\u6570\u636e\u7684\u57df\u5bbd\u548c\u7cbe\u5ea6\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">num = 123.456<\/p>\n<p>print(&#39;%10.2f&#39; % num)  # \u8f93\u51fa\uff1a    123.46<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c<code>%10.2f<\/code> \u8868\u793a\u8f93\u51fa\u4e00\u4e2a\u5bbd\u5ea6\u4e3a10\uff0c\u7cbe\u5ea6\u4e3a2\u7684\u5c0f\u6570\u3002<\/p>\n<\/p>\n<p><h3>2\u3001\u65b0\u5f0f\u7684 str.format() \u65b9\u6cd5<\/h3>\n<\/p>\n<p><p>\u65b0\u5f0f\u7684 <code>str.format()<\/code> \u65b9\u6cd5\u662fPython 3\u4e2d\u5f15\u5165\u7684\u4e00\u79cd\u66f4\u5f3a\u5927\u548c\u7075\u6d3b\u7684\u5b57\u7b26\u4e32\u683c\u5f0f\u5316\u65b9\u6cd5\u3002\u5176\u57fa\u672c\u8bed\u6cd5\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">&#39;{:[\u586b\u5145\u5b57\u7b26][\u5bf9\u9f50\u65b9\u5f0f][\u5bbd\u5ea6][,][.\u7cbe\u5ea6][\u7c7b\u578b]}&#39;.format(\u503c)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u6765\u63a7\u5236\u8f93\u51fa\u6570\u636e\u7684\u57df\u5bbd\u548c\u7cbe\u5ea6\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">num = 123.456<\/p>\n<p>print(&#39;{:10.2f}&#39;.format(num))  # \u8f93\u51fa\uff1a    123.46<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c<code>{:10.2f}<\/code> \u8868\u793a\u8f93\u51fa\u4e00\u4e2a\u5bbd\u5ea6\u4e3a10\uff0c\u7cbe\u5ea6\u4e3a2\u7684\u5c0f\u6570\u3002<\/p>\n<\/p>\n<p><h3>3\u3001f-string\uff08\u683c\u5f0f\u5316\u5b57\u7b26\u4e32\u5b57\u9762\u91cf\uff09<\/h3>\n<\/p>\n<p><p>f-string \u662fPython 3.6\u4e2d\u5f15\u5165\u7684\u4e00\u79cd\u66f4\u7b80\u6d01\u548c\u9ad8\u6548\u7684\u5b57\u7b26\u4e32\u683c\u5f0f\u5316\u65b9\u6cd5\u3002\u5176\u57fa\u672c\u8bed\u6cd5\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">f&#39;{\u503c:[\u586b\u5145\u5b57\u7b26][\u5bf9\u9f50\u65b9\u5f0f][\u5bbd\u5ea6][,][.\u7cbe\u5ea6][\u7c7b\u578b]}&#39;<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u6765\u63a7\u5236\u8f93\u51fa\u6570\u636e\u7684\u57df\u5bbd\u548c\u7cbe\u5ea6\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">num = 123.456<\/p>\n<p>print(f&#39;{num:10.2f}&#39;)  # \u8f93\u51fa\uff1a    123.46<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c<code>{num:10.2f}<\/code> \u8868\u793a\u8f93\u51fa\u4e00\u4e2a\u5bbd\u5ea6\u4e3a10\uff0c\u7cbe\u5ea6\u4e3a2\u7684\u5c0f\u6570\u3002<\/p>\n<\/p>\n<p><h2>\u4e8c\u3001\u4f7f\u7528<code>pandas<\/code>\u5e93\u8bbe\u7f6e\u663e\u793a\u9009\u9879<\/h2>\n<\/p>\n<p><p><code>pandas<\/code>\u5e93\u4e2d\u7684<code>pd.options.display<\/code>\u9009\u9879\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u63a7\u5236DataFrame\u548cSeries\u7684\u663e\u793a\u683c\u5f0f\uff0c\u5305\u62ec\u5217\u5bbd\u3001\u884c\u5bbd\u7b49\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u65b9\u6cd5\u6765\u8bbe\u7f6e<code>pandas<\/code>\u5e93\u4e2d\u7684\u57df\u5bbd\uff1a<\/p>\n<\/p>\n<p><h3>1\u3001\u8bbe\u7f6e\u5217\u5bbd<\/h3>\n<\/p>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7<code>pd.options.display.max_colwidth<\/code>\u9009\u9879\u6765\u8bbe\u7f6e\u5217\u5bbd\u3002\u5177\u4f53\u793a\u4f8b\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u793a\u4f8bDataFrame<\/strong><\/h2>\n<p>data = {&#39;A&#39;: [1, 2, 3], &#39;B&#39;: [123.456, 78.90, 12.3456]}<\/p>\n<p>df = pd.DataFrame(data)<\/p>\n<h2><strong>\u8bbe\u7f6e\u5217\u5bbd\u4e3a20<\/strong><\/h2>\n<p>pd.options.display.max_colwidth = 20<\/p>\n<h2><strong>\u663e\u793aDataFrame<\/strong><\/h2>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u5c06<code>pd.options.display.max_colwidth<\/code>\u8bbe\u7f6e\u4e3a20\uff0c\u4ece\u800c\u63a7\u5236\u4e86DataFrame\u4e2d\u5217\u7684\u663e\u793a\u5bbd\u5ea6\u3002<\/p>\n<\/p>\n<p><h3>2\u3001\u8bbe\u7f6e\u884c\u5bbd<\/h3>\n<\/p>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7<code>pd.options.display.width<\/code>\u9009\u9879\u6765\u8bbe\u7f6e\u884c\u5bbd\u3002\u5177\u4f53\u793a\u4f8b\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u793a\u4f8bDataFrame<\/strong><\/h2>\n<p>data = {&#39;A&#39;: [1, 2, 3], &#39;B&#39;: [123.456, 78.90, 12.3456]}<\/p>\n<p>df = pd.DataFrame(data)<\/p>\n<h2><strong>\u8bbe\u7f6e\u884c\u5bbd\u4e3a50<\/strong><\/h2>\n<p>pd.options.display.width = 50<\/p>\n<h2><strong>\u663e\u793aDataFrame<\/strong><\/h2>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u5c06<code>pd.options.display.width<\/code>\u8bbe\u7f6e\u4e3a50\uff0c\u4ece\u800c\u63a7\u5236\u4e86DataFrame\u4e2d\u884c\u7684\u663e\u793a\u5bbd\u5ea6\u3002<\/p>\n<\/p>\n<p><h2>\u4e09\u3001\u4f7f\u7528<code>numpy<\/code>\u5e93\u8bbe\u7f6e\u663e\u793a\u9009\u9879<\/h2>\n<\/p>\n<p><p><code>numpy<\/code>\u5e93\u4e2d\u7684<code>set_printoptions<\/code>\u65b9\u6cd5\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u63a7\u5236\u6570\u7ec4\u7684\u663e\u793a\u683c\u5f0f\uff0c\u5305\u62ec\u5c0f\u6570\u70b9\u540e\u7684\u7cbe\u5ea6\u3001\u57df\u5bbd\u7b49\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u65b9\u6cd5\u6765\u8bbe\u7f6e<code>numpy<\/code>\u5e93\u4e2d\u7684\u57df\u5bbd\uff1a<\/p>\n<\/p>\n<p><h3>1\u3001\u8bbe\u7f6e\u6d6e\u70b9\u6570\u663e\u793a\u683c\u5f0f<\/h3>\n<\/p>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7<code>numpy.set_printoptions<\/code>\u65b9\u6cd5\u4e2d\u7684<code>formatter<\/code>\u9009\u9879\u6765\u8bbe\u7f6e\u6d6e\u70b9\u6570\u7684\u663e\u793a\u683c\u5f0f\u3002\u5177\u4f53\u793a\u4f8b\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u793a\u4f8b\u6570\u7ec4<\/strong><\/h2>\n<p>arr = np.array([123.456, 78.90, 12.3456])<\/p>\n<h2><strong>\u8bbe\u7f6e\u6253\u5370\u9009\u9879<\/strong><\/h2>\n<p>np.set_printoptions(formatter={&#39;float&#39;: &#39;{:10.2f}&#39;.format})<\/p>\n<h2><strong>\u663e\u793a\u6570\u7ec4<\/strong><\/h2>\n<p>print(arr)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u901a\u8fc7<code>numpy.set_printoptions<\/code>\u65b9\u6cd5\u4e2d\u7684<code>formatter<\/code>\u9009\u9879\u5c06\u6d6e\u70b9\u6570\u7684\u663e\u793a\u683c\u5f0f\u8bbe\u7f6e\u4e3a\u5bbd\u5ea6\u4e3a10\uff0c\u7cbe\u5ea6\u4e3a2\u7684\u5c0f\u6570\u3002<\/p>\n<\/p>\n<p><h3>2\u3001\u8bbe\u7f6e\u6570\u7ec4\u7684\u663e\u793a\u5bbd\u5ea6<\/h3>\n<\/p>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7<code>numpy.set_printoptions<\/code>\u65b9\u6cd5\u4e2d\u7684<code>linewidth<\/code>\u9009\u9879\u6765\u8bbe\u7f6e\u6570\u7ec4\u7684\u663e\u793a\u5bbd\u5ea6\u3002\u5177\u4f53\u793a\u4f8b\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u793a\u4f8b\u6570\u7ec4<\/strong><\/h2>\n<p>arr = np.array([[123.456, 78.90, 12.3456], [45.678, 90.12, 34.567]])<\/p>\n<h2><strong>\u8bbe\u7f6e\u6253\u5370\u9009\u9879<\/strong><\/h2>\n<p>np.set_printoptions(linewidth=50)<\/p>\n<h2><strong>\u663e\u793a\u6570\u7ec4<\/strong><\/h2>\n<p>print(arr)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u901a\u8fc7<code>numpy.set_printoptions<\/code>\u65b9\u6cd5\u4e2d\u7684<code>linewidth<\/code>\u9009\u9879\u5c06\u6570\u7ec4\u7684\u663e\u793a\u5bbd\u5ea6\u8bbe\u7f6e\u4e3a50\u3002<\/p>\n<\/p>\n<p><h2>\u603b\u7ed3<\/h2>\n<\/p>\n<p><p>\u5728Python\u4e2d\u8bbe\u7f6e\u6570\u636e\u7684\u57df\u5bbd\u6709\u591a\u79cd\u65b9\u6cd5\uff0c\u5305\u62ec\u4f7f\u7528\u5b57\u7b26\u4e32\u683c\u5f0f\u5316\u65b9\u6cd5\u3001\u4f7f\u7528<code>pandas<\/code>\u5e93\u4e2d\u7684<code>pd.options.display<\/code>\u8bbe\u7f6e\u3001\u4ee5\u53ca\u4f7f\u7528<code>numpy<\/code>\u5e93\u4e2d\u7684<code>set_printoptions<\/code>\u65b9\u6cd5\u3002\u8fd9\u4e9b\u65b9\u6cd5\u5404\u6709\u4f18\u52a3\uff0c\u9002\u7528\u4e8e\u4e0d\u540c\u7684\u573a\u666f\u3002\u901a\u8fc7\u7075\u6d3b\u8fd0\u7528\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u66f4\u597d\u5730\u63a7\u5236\u6570\u636e\u7684\u663e\u793a\u683c\u5f0f\uff0c\u4ece\u800c\u63d0\u9ad8\u6570\u636e\u5904\u7406\u548c\u5c55\u793a\u7684\u6548\u679c\u3002<\/p>\n<\/p>\n<p><p>\u65e0\u8bba\u662f\u5904\u7406\u7b80\u5355\u7684\u5b57\u7b26\u4e32\u8f93\u51fa\uff0c\u8fd8\u662f\u5904\u7406\u590d\u6742\u7684\u6570\u636e\u6846\u548c\u6570\u7ec4\uff0c\u638c\u63e1\u6570\u636e\u57df\u5bbd\u7684\u8bbe\u7f6e\u65b9\u6cd5\u90fd\u662f\u975e\u5e38\u91cd\u8981\u7684\u6280\u80fd\u3002\u5e0c\u671b\u901a\u8fc7\u672c\u6587\u7684\u4ecb\u7ecd\uff0c\u60a8\u80fd\u591f\u66f4\u597d\u5730\u7406\u89e3\u548c\u5e94\u7528\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u63d0\u5347\u6570\u636e\u5904\u7406\u7684\u80fd\u529b\u548c\u6548\u7387\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u8c03\u6574\u6570\u636e\u7684\u57df\u5bbd\u4ee5\u6ee1\u8db3\u7279\u5b9a\u9700\u6c42\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u8c03\u6574\u6570\u636e\u7684\u57df\u5bbd\u901a\u5e38\u6d89\u53ca\u5230\u6570\u636e\u7684\u5904\u7406\u548c\u53ef\u89c6\u5316\u3002\u53ef\u4ee5\u4f7f\u7528\u5e93\u5982NumPy\u548cPandas\u6765\u5904\u7406\u6570\u636e\uff0c\u800c\u5728\u53ef\u89c6\u5316\u65f6\uff0c\u53ef\u4ee5\u5229\u7528Matplotlib\u6216Seaborn\u3002\u8c03\u6574\u57df\u5bbd\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u6570\u636e\u7684\u8303\u56f4\u3001\u8fc7\u6ee4\u6570\u636e\u6216\u5f52\u4e00\u5316\u6570\u636e\u6765\u5b9e\u73b0\u3002\u4f8b\u5982\uff0c\u4f7f\u7528Pandas\u7684<code>.clip()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u8f7b\u677e\u9650\u5236\u6570\u636e\u7684\u6700\u5927\u548c\u6700\u5c0f\u503c\uff0c\u4ee5\u6b64\u6765\u8c03\u6574\u57df\u5bbd\u3002<\/p>\n<p><strong>\u5728\u6570\u636e\u53ef\u89c6\u5316\u4e2d\uff0c\u5982\u4f55\u6709\u6548\u8bbe\u7f6e\u5750\u6807\u8f74\u7684\u57df\u5bbd\uff1f<\/strong><br \/>\u5728\u6570\u636e\u53ef\u89c6\u5316\u4e2d\uff0c\u8bbe\u7f6e\u5750\u6807\u8f74\u7684\u57df\u5bbd\u662f\u975e\u5e38\u91cd\u8981\u7684\uff0c\u53ef\u4ee5\u901a\u8fc7Matplotlib\u7684<code>set_xlim()<\/code>\u548c<code>set_ylim()<\/code>\u65b9\u6cd5\u6765\u5b9a\u4e49X\u8f74\u548cY\u8f74\u7684\u8303\u56f4\u3002\u6b64\u5916\uff0c\u4f7f\u7528Seaborn\u7ed8\u5236\u56fe\u8868\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u4f20\u9012<code>xlim<\/code>\u548c<code>ylim<\/code>\u53c2\u6570\u6765\u63a7\u5236\u57df\u5bbd\u3002\u8fd9\u79cd\u8bbe\u7f6e\u53ef\u4ee5\u5e2e\u52a9\u7a81\u51fa\u6570\u636e\u7684\u7279\u5b9a\u90e8\u5206\uff0c\u589e\u5f3a\u56fe\u8868\u7684\u53ef\u8bfb\u6027\u3002<\/p>\n<p><strong>\u662f\u5426\u6709\u65b9\u6cd5\u53ef\u4ee5\u81ea\u52a8\u5316\u6570\u636e\u57df\u5bbd\u7684\u8bbe\u7f6e\uff1f<\/strong><br \/>\u662f\u7684\uff0c\u53ef\u4ee5\u4f7f\u7528\u7edf\u8ba1\u65b9\u6cd5\u6765\u81ea\u52a8\u5316\u6570\u636e\u57df\u5bbd\u7684\u8bbe\u7f6e\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u8ba1\u7b97\u6570\u636e\u7684\u6807\u51c6\u5dee\u548c\u5747\u503c\uff0c\u7136\u540e\u6839\u636e\u8fd9\u4e9b\u7edf\u8ba1\u91cf\u6765\u52a8\u6001\u8c03\u6574\u57df\u5bbd\u3002\u5229\u7528Python\u7684\u7edf\u8ba1\u5e93\uff0c\u53ef\u4ee5\u5b9e\u73b0\u81ea\u52a8\u5316\u8bbe\u7f6e\uff0c\u786e\u4fdd\u6570\u636e\u5728\u56fe\u8868\u4e2d\u4ee5\u6700\u4f73\u65b9\u5f0f\u5448\u73b0\u3002\u6b64\u65b9\u6cd5\u4e0d\u4ec5\u63d0\u9ad8\u4e86\u6548\u7387\uff0c\u8fd8\u80fd\u786e\u4fdd\u5c55\u793a\u7684\u51c6\u786e\u6027\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\u8bbe\u7f6e\u6570\u636e\u7684\u57df\u5bbd\uff0c\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528\u5b57\u7b26\u4e32\u7684\u683c\u5f0f\u5316\u65b9\u6cd5\u3001\u4f7f\u7528pandas\u5e93\u4e2d\u7684pd.options.d [&hellip;]","protected":false},"author":3,"featured_media":1088775,"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\/1088765"}],"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=1088765"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1088765\/revisions"}],"predecessor-version":[{"id":1088780,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1088765\/revisions\/1088780"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1088775"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1088765"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1088765"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1088765"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}