{"id":1054833,"date":"2024-12-31T14:45:36","date_gmt":"2024-12-31T06:45:36","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1054833.html"},"modified":"2024-12-31T14:45:38","modified_gmt":"2024-12-31T06:45:38","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e6%89%93%e5%8d%b0%e6%88%90%e7%bb%a9%e8%a1%a8","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1054833.html","title":{"rendered":"\u5982\u4f55\u7528python\u6253\u5370\u6210\u7ee9\u8868"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-docs.pingcode.com\/wp-content\/uploads\/2024\/12\/f899fb0b-acc7-40a9-bf54-0d087480cfb7.webp?x-oss-process=image\/auto-orient,1\/format,webp\" alt=\"\u5982\u4f55\u7528python\u6253\u5370\u6210\u7ee9\u8868\" \/><\/p>\n<p><p> <strong>\u5982\u4f55\u7528Python\u6253\u5370\u6210\u7ee9\u8868\uff1f<\/strong><\/p>\n<\/p>\n<p><p><strong>\u4f7f\u7528Python\u6253\u5370\u6210\u7ee9\u8868\u7684\u65b9\u6cd5\u6709\u5f88\u591a\u79cd\uff0c\u4f8b\u5982\u4f7f\u7528print\u8bed\u53e5\u3001\u683c\u5f0f\u5316\u5b57\u7b26\u4e32\u3001Pandas\u5e93\u7b49<\/strong>\u3002\u5176\u4e2d\uff0c\u4f7f\u7528Pandas\u5e93\u662f\u6700\u4fbf\u6377\u4e14\u529f\u80fd\u5f3a\u5927\u7684\u65b9\u6cd5\u3002Pandas\u5e93\u53ef\u4ee5\u65b9\u4fbf\u5730\u5904\u7406\u6570\u636e\u3001\u8fdb\u884c\u6570\u636e\u5206\u6790\uff0c\u5e76\u80fd\u4ee5\u8868\u683c\u5f62\u5f0f\u8f93\u51fa\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Pandas\u5e93\u6765\u6253\u5370\u6210\u7ee9\u8868\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u5b89\u88c5\u548c\u5bfc\u5165Pandas\u5e93<\/h3>\n<\/p>\n<p><p>\u5728\u4f7f\u7528Pandas\u5e93\u524d\uff0c\u9996\u5148\u9700\u8981\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86\u8be5\u5e93\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5Pandas\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">pip install pandas<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u5bfc\u5165Pandas\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e8c\u3001\u521b\u5efa\u6570\u636e<\/h3>\n<\/p>\n<p><p>\u63a5\u4e0b\u6765\uff0c\u521b\u5efa\u4e00\u4e2a\u5305\u542b\u5b66\u751f\u6210\u7ee9\u6570\u636e\u7684\u5b57\u5178\u3002\u5b57\u5178\u7684\u952e\u662f\u5217\u540d\uff0c\u503c\u662f\u5217\u4e2d\u7684\u6570\u636e\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">data = {<\/p>\n<p>    &#39;Name&#39;: [&#39;Alice&#39;, &#39;Bob&#39;, &#39;Charlie&#39;, &#39;David&#39;],<\/p>\n<p>    &#39;Math&#39;: [85, 90, 78, 92],<\/p>\n<p>    &#39;Science&#39;: [88, 76, 95, 89],<\/p>\n<p>    &#39;English&#39;: [91, 85, 82, 90]<\/p>\n<p>}<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e09\u3001\u5c06\u6570\u636e\u8f6c\u6362\u4e3aDataFrame<\/h3>\n<\/p>\n<p><p>\u5c06\u6570\u636e\u5b57\u5178\u8f6c\u6362\u4e3aPandas\u7684DataFrame\u5bf9\u8c61\uff0c\u8fd9\u662fPandas\u4e2d\u6700\u57fa\u672c\u7684\u6570\u636e\u7ed3\u6784\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">df = pd.DataFrame(data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u56db\u3001\u6253\u5370\u6210\u7ee9\u8868<\/h3>\n<\/p>\n<p><p>\u4f7f\u7528Pandas\u5e93\u7684<code>print<\/code>\u529f\u80fd\uff0c\u53ef\u4ee5\u8f7b\u677e\u6253\u5370\u51fa\u6210\u7ee9\u8868\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8f93\u51fa\u7ed3\u679c\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code>       Name  Math  Science  English<\/p>\n<p>0     Alice    85       88       91<\/p>\n<p>1       Bob    90       76       85<\/p>\n<p>2   Charlie    78       95       82<\/p>\n<p>3     David    92       89       90<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e94\u3001\u683c\u5f0f\u5316\u8f93\u51fa<\/h3>\n<\/p>\n<p><p>\u4e3a\u4e86\u4f7f\u8f93\u51fa\u7684\u6210\u7ee9\u8868\u66f4\u52a0\u7f8e\u89c2\uff0c\u53ef\u4ee5\u8bbe\u7f6eDataFrame\u7684\u4e00\u4e9b\u5c5e\u6027\uff0c\u4f8b\u5982\u5217\u5bbd\u3001\u5bf9\u9f50\u65b9\u5f0f\u7b49\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">pd.set_option(&#39;display.width&#39;, 100)<\/p>\n<p>pd.set_option(&#39;display.colheader_justify&#39;, &#39;center&#39;)<\/p>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u516d\u3001\u6dfb\u52a0\u603b\u5206\u548c\u5e73\u5747\u5206<\/h3>\n<\/p>\n<p><p>\u4e3a\u4e86\u66f4\u5168\u9762\u5730\u5c55\u793a\u5b66\u751f\u6210\u7ee9\uff0c\u53ef\u4ee5\u6dfb\u52a0\u603b\u5206\u548c\u5e73\u5747\u5206\u5217\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">df[&#39;Total&#39;] = df[[&#39;Math&#39;, &#39;Science&#39;, &#39;English&#39;]].sum(axis=1)<\/p>\n<p>df[&#39;Average&#39;] = df[[&#39;Math&#39;, &#39;Science&#39;, &#39;English&#39;]].mean(axis=1)<\/p>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8f93\u51fa\u7ed3\u679c\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code>       Name  Math  Science  English  Total    Average<\/p>\n<p>0     Alice    85       88       91    264  88.000000<\/p>\n<p>1       Bob    90       76       85    251  83.666667<\/p>\n<p>2   Charlie    78       95       82    255  85.000000<\/p>\n<p>3     David    92       89       90    271  90.333333<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e03\u3001\u4fdd\u5b58\u6210\u7ee9\u8868\u5230\u6587\u4ef6<\/h3>\n<\/p>\n<p><p>\u5982\u679c\u9700\u8981\u5c06\u6210\u7ee9\u8868\u4fdd\u5b58\u5230\u6587\u4ef6\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u7684<code>to_csv<\/code>\u65b9\u6cd5\u5c06DataFrame\u4fdd\u5b58\u4e3aCSV\u6587\u4ef6\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">df.to_csv(&#39;grades.csv&#39;, index=False)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u6837\u5c31\u4f1a\u5728\u5f53\u524d\u76ee\u5f55\u4e0b\u751f\u6210\u4e00\u4e2a\u540d\u4e3a<code>grades.csv<\/code>\u7684\u6587\u4ef6\uff0c\u5185\u5bb9\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code>Name,Math,Science,English,Total,Average<\/p>\n<p>Alice,85,88,91,264,88.0<\/p>\n<p>Bob,90,76,85,251,83.66666666666667<\/p>\n<p>Charlie,78,95,82,255,85.0<\/p>\n<p>David,92,89,90,271,90.33333333333333<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u516b\u3001\u8bfb\u53d6\u6587\u4ef6\u5e76\u6253\u5370\u6210\u7ee9\u8868<\/h3>\n<\/p>\n<p><p>\u8fd8\u53ef\u4ee5\u4f7f\u7528Pandas\u8bfb\u53d6CSV\u6587\u4ef6\u5e76\u6253\u5370\u6210\u7ee9\u8868\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">df_from_file = pd.read_csv(&#39;grades.csv&#39;)<\/p>\n<p>print(df_from_file)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8f93\u51fa\u7ed3\u679c\u4e0e\u4e4b\u524d\u76f8\u540c\uff1a<\/p>\n<\/p>\n<p><pre><code>       Name  Math  Science  English  Total    Average<\/p>\n<p>0     Alice    85       88       91    264  88.000000<\/p>\n<p>1       Bob    90       76       85    251  83.666667<\/p>\n<p>2   Charlie    78       95       82    255  85.000000<\/p>\n<p>3     David    92       89       90    271  90.333333<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e5d\u3001\u4f7f\u7528\u6837\u5f0f\u4f7f\u6210\u7ee9\u8868\u66f4\u52a0\u7f8e\u89c2<\/h3>\n<\/p>\n<p><p>Pandas\u63d0\u4f9b\u4e86\u6837\u5f0fAPI\uff0c\u53ef\u4ee5\u4e3aDataFrame\u6dfb\u52a0\u6837\u5f0f\uff0c\u4f7f\u6210\u7ee9\u8868\u66f4\u52a0\u7f8e\u89c2\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">styled_df = df.style.set_table_styles(<\/p>\n<p>    [{&#39;selector&#39;: &#39;thead th&#39;, &#39;props&#39;: [(&#39;background-color&#39;, &#39;#D5DBDB&#39;)]}]<\/p>\n<p>).set_properties({&#39;text-align&#39;: &#39;center&#39;}).hide_index()<\/p>\n<p>styled_df<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7Jupyter Notebook\u6216IPython\u73af\u5883\uff0c\u53ef\u4ee5\u76f4\u89c2\u5730\u67e5\u770b\u5e26\u6837\u5f0f\u7684\u6210\u7ee9\u8868\u3002<\/p>\n<\/p>\n<p><h3>\u5341\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p><strong>\u4f7f\u7528Pandas\u5e93\u662f\u6253\u5370\u6210\u7ee9\u8868\u7684\u4fbf\u6377\u65b9\u6cd5<\/strong>\u3002\u901a\u8fc7\u521b\u5efa\u6570\u636e\u3001\u8f6c\u6362\u4e3aDataFrame\u3001\u6253\u5370\u548c\u4fdd\u5b58\u6210\u7ee9\u8868\uff0c\u53ef\u4ee5\u8f7b\u677e\u5b8c\u6210\u6210\u7ee9\u8868\u7684\u8f93\u51fa\u3002Pandas\u8fd8\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\uff0c\u4f8b\u5982\u683c\u5f0f\u5316\u3001\u6837\u5f0f\u3001\u4fdd\u5b58\u548c\u8bfb\u53d6\u6587\u4ef6\u7b49\uff0c\u4f7f\u5f97\u5904\u7406\u6570\u636e\u53d8\u5f97\u66f4\u52a0\u9ad8\u6548\u548c\u7f8e\u89c2\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u4f7f\u7528Python\u751f\u6210\u5e26\u6709\u683c\u5f0f\u7684\u6210\u7ee9\u8868\uff1f<\/strong><br \/>\u8981\u751f\u6210\u683c\u5f0f\u826f\u597d\u7684\u6210\u7ee9\u8868\uff0c\u53ef\u4ee5\u4f7f\u7528Python\u7684<code>pandas<\/code>\u5e93\u6765\u5904\u7406\u6570\u636e\uff0c\u5e76\u7528<code>tabulate<\/code>\u5e93\u6765\u7f8e\u5316\u8f93\u51fa\u3002\u9996\u5148\uff0c\u786e\u4fdd\u5b89\u88c5\u4e86\u8fd9\u4e24\u4e2a\u5e93\u3002\u7136\u540e\uff0c\u53ef\u4ee5\u521b\u5efa\u4e00\u4e2aDataFrame\u5e76\u4f7f\u7528<code>print<\/code>\u51fd\u6570\u7ed3\u5408<code>tabulate<\/code>\u6765\u663e\u793a\u6210\u7ee9\u8868\u3002\u8fd9\u6837\u7684\u65b9\u5f0f\u4e0d\u4ec5\u7f8e\u89c2\uff0c\u8fd8\u80fd\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u5206\u6790\u3002<\/p>\n<p><strong>\u5728Python\u4e2d\u5982\u4f55\u8bfb\u53d6\u548c\u5b58\u50a8\u6210\u7ee9\u6570\u636e\uff1f<\/strong><br \/>\u53ef\u4ee5\u4f7f\u7528<code>pandas<\/code>\u5e93\u6765\u8bfb\u53d6\u548c\u5b58\u50a8\u6210\u7ee9\u6570\u636e\u3002\u901a\u8fc7\u8bfb\u53d6CSV\u6587\u4ef6\u6216Excel\u6587\u4ef6\uff0c\u53ef\u4ee5\u8f7b\u677e\u52a0\u8f7d\u6210\u7ee9\u6570\u636e\u3002\u5b58\u50a8\u65f6\uff0c\u53ef\u4ee5\u5c06DataFrame\u5bfc\u51fa\u4e3aCSV\u6216Excel\u683c\u5f0f\uff0c\u65b9\u4fbf\u540e\u7eed\u4f7f\u7528\u548c\u5171\u4eab\u3002<\/p>\n<p><strong>\u5982\u4f55\u5728\u6210\u7ee9\u8868\u4e2d\u6dfb\u52a0\u8ba1\u7b97\u529f\u80fd\uff0c\u6bd4\u5982\u5e73\u5747\u5206\u548c\u603b\u5206\uff1f<\/strong><br \/>\u4f7f\u7528<code>pandas<\/code>\u5e93\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u5bf9\u6210\u7ee9\u6570\u636e\u8fdb\u884c\u8ba1\u7b97\u3002\u901a\u8fc7<code>DataFrame<\/code>\u5bf9\u8c61\uff0c\u53ef\u4ee5\u4f7f\u7528\u5185\u7f6e\u7684\u51fd\u6570\u5982<code>mean()<\/code>\u548c<code>sum()<\/code>\u6765\u8ba1\u7b97\u5e73\u5747\u5206\u548c\u603b\u5206\u3002\u5c06\u8fd9\u4e9b\u8ba1\u7b97\u7ed3\u679c\u6dfb\u52a0\u5230\u6210\u7ee9\u8868\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u6210\u7ee9\u8868\u66f4\u52a0\u5168\u9762\u548c\u5b9e\u7528\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5982\u4f55\u7528Python\u6253\u5370\u6210\u7ee9\u8868\uff1f \u4f7f\u7528Python\u6253\u5370\u6210\u7ee9\u8868\u7684\u65b9\u6cd5\u6709\u5f88\u591a\u79cd\uff0c\u4f8b\u5982\u4f7f\u7528print\u8bed\u53e5\u3001\u683c\u5f0f\u5316\u5b57\u7b26\u4e32 [&hellip;]","protected":false},"author":3,"featured_media":1054845,"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\/1054833"}],"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=1054833"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1054833\/revisions"}],"predecessor-version":[{"id":1054847,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1054833\/revisions\/1054847"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1054845"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1054833"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1054833"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1054833"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}