{"id":1037238,"date":"2024-12-31T12:13:31","date_gmt":"2024-12-31T04:13:31","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1037238.html"},"modified":"2024-12-31T12:13:34","modified_gmt":"2024-12-31T04:13:34","slug":"python%e5%a6%82%e4%bd%95%e6%a0%b9%e6%8d%ae%e7%b4%a2%e5%bc%95%e5%8f%b7%e8%8e%b7%e5%8f%96%e5%88%97%e6%95%b0%e6%8d%ae","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1037238.html","title":{"rendered":"python\u5982\u4f55\u6839\u636e\u7d22\u5f15\u53f7\u83b7\u53d6\u5217\u6570\u636e"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-docs.pingcode.com\/wp-content\/uploads\/2024\/12\/bf8f30de-d7fd-4be7-a503-a479a4ee25ec.webp?x-oss-process=image\/auto-orient,1\/format,webp\" alt=\"python\u5982\u4f55\u6839\u636e\u7d22\u5f15\u53f7\u83b7\u53d6\u5217\u6570\u636e\" \/><\/p>\n<p><p> <strong>\u5728Python\u4e2d\uff0c\u6709\u591a\u79cd\u65b9\u6cd5\u53ef\u4ee5\u6839\u636e\u7d22\u5f15\u53f7\u83b7\u53d6\u5217\u6570\u636e\u3002\u4e3b\u8981\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528Pandas\u5e93\u3001NumPy\u5e93\u4ee5\u53ca\u539f\u751f\u7684Python\u5217\u8868\u3002<\/strong> \u8fd9\u7bc7\u6587\u7ae0\u5c06\u4ecb\u7ecd\u51e0\u79cd\u5e38\u89c1\u7684\u65b9\u6cd5\uff0c\u5e76\u8be6\u7ec6\u63cf\u8ff0\u5982\u4f55\u4f7f\u7528Pandas\u6765\u5b9e\u73b0\u8fd9\u4e2a\u4efb\u52a1\u3002<\/p>\n<\/p>\n<p><h3>\u4f7f\u7528Pandas\u5e93<\/h3>\n<\/p>\n<p><p>Pandas\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u548c\u64cd\u4f5c\u5de5\u5177\uff0c\u7279\u522b\u9002\u7528\u4e8e\u5904\u7406\u8868\u683c\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u4f7f\u7528Pandas\u6839\u636e\u7d22\u5f15\u53f7\u83b7\u53d6\u5217\u6570\u636e\u7684\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n<p><h4>1\u3001\u8bfb\u53d6\u6570\u636e<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u60a8\u9700\u8981\u5bfc\u5165Pandas\u5e93\u5e76\u8bfb\u53d6\u6570\u636e\u3002\u53ef\u4ee5\u4f7f\u7528<code>pandas.read_csv<\/code>\u8bfb\u53d6CSV\u6587\u4ef6\uff0c\u6216\u8005\u4f7f\u7528<code>pandas.DataFrame<\/code>\u76f4\u63a5\u521b\u5efa\u6570\u636e\u6846\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u901a\u8fc7CSV\u6587\u4ef6\u8bfb\u53d6\u6570\u636e<\/strong><\/h2>\n<p>df = pd.read_csv(&#39;data.csv&#39;)<\/p>\n<h2><strong>\u6216\u8005\u76f4\u63a5\u521b\u5efaDataFrame<\/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>    &#39;C&#39;: [7, 8, 9]<\/p>\n<p>}<\/p>\n<p>df = pd.DataFrame(data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u6839\u636e\u7d22\u5f15\u53f7\u83b7\u53d6\u5217\u6570\u636e<\/h4>\n<\/p>\n<p><p>\u5728Pandas\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528<code>iloc<\/code>\u5c5e\u6027\u6839\u636e\u7d22\u5f15\u53f7\u6765\u83b7\u53d6\u5217\u6570\u636e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u83b7\u53d6\u7b2c1\u5217\u7684\u6570\u636e\uff08\u7d22\u5f15\u4ece0\u5f00\u59cb\uff09<\/p>\n<p>column_data = df.iloc[:, 1]<\/p>\n<p>print(column_data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0c<code>df.iloc[:, 1]<\/code>\u8868\u793a\u83b7\u53d6\u6240\u6709\u884c\u7684\u7b2c1\u5217\u6570\u636e\u3002<code>iloc<\/code>\u5c5e\u6027\u53ef\u4ee5\u7528\u4e8e\u6309\u4f4d\u7f6e\u9009\u62e9\u6570\u636e\uff0c\u5305\u62ec\u884c\u548c\u5217\u3002<\/p>\n<\/p>\n<p><p><strong>\u8be6\u7ec6\u63cf\u8ff0\uff1a<\/strong><\/p>\n<\/p>\n<p><p>\u4f7f\u7528<code>iloc<\/code>\u7684\u53e6\u4e00\u4e2a\u4f18\u52bf\u662f\u5b83\u975e\u5e38\u7075\u6d3b\uff0c\u53ef\u4ee5\u7528\u4e8e\u9009\u62e9\u7279\u5b9a\u7684\u884c\u548c\u5217\u3002\u6bd4\u5982\uff0c\u60a8\u53ef\u4ee5\u9009\u62e9\u7b2c2\u5230\u7b2c4\u884c\u548c\u7b2c1\u5230\u7b2c3\u5217\u7684\u6570\u636e\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">subset_data = df.iloc[1:4, 0:3]<\/p>\n<p>print(subset_data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4f7f\u7528NumPy\u5e93<\/h3>\n<\/p>\n<p><p>NumPy\u662f\u53e6\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u5e93\uff0c\u7279\u522b\u9002\u7528\u4e8e\u6570\u503c\u8ba1\u7b97\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u4f7f\u7528NumPy\u6839\u636e\u7d22\u5f15\u53f7\u83b7\u53d6\u5217\u6570\u636e\u7684\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n<p><h4>1\u3001\u8bfb\u53d6\u6570\u636e<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u60a8\u9700\u8981\u5bfc\u5165NumPy\u5e93\u5e76\u8bfb\u53d6\u6570\u636e\u3002\u53ef\u4ee5\u4f7f\u7528<code>numpy.array<\/code>\u76f4\u63a5\u521b\u5efa\u6570\u7ec4\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efaNumPy\u6570\u7ec4<\/strong><\/h2>\n<p>data = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u6839\u636e\u7d22\u5f15\u53f7\u83b7\u53d6\u5217\u6570\u636e<\/h4>\n<\/p>\n<p><p>\u5728NumPy\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u6570\u7ec4\u7684\u5207\u7247\u64cd\u4f5c\u6765\u83b7\u53d6\u5217\u6570\u636e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u83b7\u53d6\u7b2c1\u5217\u7684\u6570\u636e\uff08\u7d22\u5f15\u4ece0\u5f00\u59cb\uff09<\/p>\n<p>column_data = data[:, 1]<\/p>\n<p>print(column_data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0c<code>data[:, 1]<\/code>\u8868\u793a\u83b7\u53d6\u6240\u6709\u884c\u7684\u7b2c1\u5217\u6570\u636e\u3002NumPy\u7684\u5207\u7247\u64cd\u4f5c\u975e\u5e38\u9ad8\u6548\uff0c\u9002\u7528\u4e8e\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u3002<\/p>\n<\/p>\n<p><h3>\u4f7f\u7528\u539f\u751fPython\u5217\u8868<\/h3>\n<\/p>\n<p><p>\u5982\u679c\u60a8\u7684\u6570\u636e\u91cf\u4e0d\u5927\uff0c\u4e5f\u53ef\u4ee5\u4f7f\u7528\u539f\u751f\u7684Python\u5217\u8868\u6765\u5b9e\u73b0\u8fd9\u4e2a\u4efb\u52a1\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u4f7f\u7528Python\u5217\u8868\u6839\u636e\u7d22\u5f15\u53f7\u83b7\u53d6\u5217\u6570\u636e\u7684\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n<p><h4>1\u3001\u521b\u5efa\u6570\u636e<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u60a8\u9700\u8981\u521b\u5efa\u4e00\u4e2a\u5d4c\u5957\u5217\u8868\u6765\u8868\u793a\u6570\u636e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u521b\u5efa\u5d4c\u5957\u5217\u8868<\/p>\n<p>data = [<\/p>\n<p>    [1, 2, 3],<\/p>\n<p>    [4, 5, 6],<\/p>\n<p>    [7, 8, 9]<\/p>\n<p>]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u6839\u636e\u7d22\u5f15\u53f7\u83b7\u53d6\u5217\u6570\u636e<\/h4>\n<\/p>\n<p><p>\u5728Python\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u5217\u8868\u89e3\u6790\u6765\u83b7\u53d6\u5217\u6570\u636e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u83b7\u53d6\u7b2c1\u5217\u7684\u6570\u636e\uff08\u7d22\u5f15\u4ece0\u5f00\u59cb\uff09<\/p>\n<p>column_data = [row[1] for row in data]<\/p>\n<p>print(column_data)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0c\u5217\u8868\u89e3\u6790<code>[row[1] for row in data]<\/code>\u8868\u793a\u904d\u5386\u6bcf\u4e00\u884c\u5e76\u83b7\u53d6\u7b2c1\u5217\u7684\u6570\u636e\u3002\u8fd9\u79cd\u65b9\u6cd5\u7b80\u5355\u76f4\u89c2\uff0c\u9002\u7528\u4e8e\u5c0f\u89c4\u6a21\u6570\u636e\u5904\u7406\u3002<\/p>\n<\/p>\n<p><h3>\u7ed3\u8bba<\/h3>\n<\/p>\n<p><p>\u6839\u636e\u7d22\u5f15\u53f7\u83b7\u53d6\u5217\u6570\u636e\u5728\u6570\u636e\u5206\u6790\u548c\u5904\u7406\u8fc7\u7a0b\u4e2d\u975e\u5e38\u5e38\u89c1\u3002<strong>\u4f7f\u7528Pandas\u5e93\u3001NumPy\u5e93\u548c\u539f\u751fPython\u5217\u8868\u90fd\u53ef\u4ee5\u5b9e\u73b0\u8fd9\u4e00\u4efb\u52a1\uff0c\u4f46Pandas\u548cNumPy\u66f4\u9002\u7528\u4e8e\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u3002<\/strong> Pandas\u7684<code>iloc<\/code>\u5c5e\u6027\u548cNumPy\u7684\u5207\u7247\u64cd\u4f5c\u63d0\u4f9b\u4e86\u7075\u6d3b\u9ad8\u6548\u7684\u89e3\u51b3\u65b9\u6848\uff0c\u800c\u539f\u751fPython\u5217\u8868\u89e3\u6790\u5219\u9002\u7528\u4e8e\u7b80\u5355\u573a\u666f\u3002\u6839\u636e\u60a8\u7684\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\uff0c\u53ef\u4ee5\u663e\u8457\u63d0\u9ad8\u6570\u636e\u5904\u7406\u7684\u6548\u7387\u548c\u51c6\u786e\u6027\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528\u7d22\u5f15\u53f7\u83b7\u53d6DataFrame\u7684\u5217\u6570\u636e\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u4f7f\u7528Pandas\u5e93\u53ef\u4ee5\u975e\u5e38\u65b9\u4fbf\u5730\u6839\u636e\u7d22\u5f15\u53f7\u83b7\u53d6DataFrame\u7684\u5217\u6570\u636e\u3002\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u7684\u6570\u636e\u5df2\u7ecf\u88ab\u52a0\u8f7d\u5230\u4e00\u4e2aDataFrame\u4e2d\u3002\u7136\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528<code>iloc<\/code>\u65b9\u6cd5\uff0c\u4f20\u5165\u5bf9\u5e94\u7684\u5217\u7d22\u5f15\u53f7\uff0c\u4f8b\u5982<code>df.iloc[:, index_number]<\/code>\uff0c\u5176\u4e2d<code>index_number<\/code>\u4e3a\u4f60\u60f3\u8981\u83b7\u53d6\u7684\u5217\u7684\u7d22\u5f15\u3002\u8fd9\u6837\u5c31\u80fd\u83b7\u53d6\u6307\u5b9a\u5217\u7684\u6570\u636e\u3002<\/p>\n<p><strong>\u5982\u679c\u6211\u53ea\u77e5\u9053\u5217\u540d\uff0c\u662f\u5426\u53ef\u4ee5\u901a\u8fc7\u5217\u540d\u83b7\u53d6\u6570\u636e\uff1f<\/strong><br \/>\u5f53\u7136\u53ef\u4ee5\uff01\u5982\u679c\u4f60\u77e5\u9053\u5217\u7684\u540d\u79f0\uff0c\u53ef\u4ee5\u76f4\u63a5\u4f7f\u7528DataFrame\u5bf9\u8c61\u7684\u5217\u540d\u6765\u8bbf\u95ee\u6570\u636e\u3002\u4f8b\u5982\uff0c\u4f7f\u7528<code>df[&#39;column_name&#39;]<\/code>\u53ef\u4ee5\u83b7\u53d6\u5bf9\u5e94\u5217\u7684\u6570\u636e\u3002\u8fd9\u79cd\u65b9\u5f0f\u975e\u5e38\u76f4\u89c2\uff0c\u5c24\u5176\u5728\u5904\u7406\u5927\u6570\u636e\u96c6\u65f6\uff0c\u4f7f\u7528\u5217\u540d\u80fd\u591f\u5e2e\u52a9\u4f60\u66f4\u5feb\u5b9a\u4f4d\u5230\u9700\u8981\u7684\u6570\u636e\u3002<\/p>\n<p><strong>\u5982\u4f55\u5904\u7406\u7d22\u5f15\u53f7\u8d85\u51fa\u8303\u56f4\u7684\u60c5\u51b5\uff1f<\/strong><br \/>\u5728\u4f7f\u7528\u7d22\u5f15\u53f7\u83b7\u53d6\u5217\u6570\u636e\u65f6\uff0c\u5982\u679c\u7d22\u5f15\u8d85\u51fa\u4e86DataFrame\u7684\u5217\u6570\u8303\u56f4\uff0c\u4f1a\u5f15\u53d1<code>IndexError<\/code>\u3002\u4e3a\u907f\u514d\u8fd9\u79cd\u60c5\u51b5\uff0c\u53ef\u4ee5\u5728\u8bbf\u95ee\u4e4b\u524d\u68c0\u67e5DataFrame\u7684\u5217\u6570\uff0c\u53ef\u4ee5\u4f7f\u7528<code>len(df.columns)<\/code>\u6765\u83b7\u53d6\u5217\u7684\u6570\u91cf\uff0c\u786e\u4fdd\u4f60\u7684\u7d22\u5f15\u5728\u5408\u6cd5\u8303\u56f4\u5185\u3002\u82e5\u4e0d\u786e\u5b9a\uff0c\u53ef\u4ee5\u4f7f\u7528\u6761\u4ef6\u8bed\u53e5\u6765\u907f\u514d\u9519\u8bef\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u6709\u591a\u79cd\u65b9\u6cd5\u53ef\u4ee5\u6839\u636e\u7d22\u5f15\u53f7\u83b7\u53d6\u5217\u6570\u636e\u3002\u4e3b\u8981\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528Pandas\u5e93\u3001NumPy\u5e93\u4ee5\u53ca\u539f\u751f\u7684P [&hellip;]","protected":false},"author":3,"featured_media":1037250,"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\/1037238"}],"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=1037238"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1037238\/revisions"}],"predecessor-version":[{"id":1037253,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1037238\/revisions\/1037253"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1037250"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1037238"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1037238"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1037238"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}