{"id":1518,"date":"2023-07-26T01:35:25","date_gmt":"2023-07-26T01:35:25","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e5%88%97%e8%a1%a8%e5%88%b0%e6%95%b0%e6%8d%ae%e6%a1%86-python\/"},"modified":"2023-07-26T01:35:25","modified_gmt":"2023-07-26T01:35:25","slug":"%e5%88%97%e8%a1%a8%e5%88%b0%e6%95%b0%e6%8d%ae%e6%a1%86-python","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e5%88%97%e8%a1%a8%e5%88%b0%e6%95%b0%e6%8d%ae%e6%a1%86-python\/","title":{"rendered":"\u5982\u4f55\u5728 python \u4e2d\u5c06\u5217\u8868\u8f6c\u6362\u4e3a dataframe"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u901a\u5e38\uff0c\u60a8\u53ef\u80fd\u5e0c\u671b\u5728 Python \u4e2d\u5c06 List \u8f6c\u6362\u4e3a DataFrame\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5e78\u8fd0\u7684\u662f\uff0c\u4f7f\u7528<a href=\"https:\/\/pandas.pydata.org\/pandas-docs\/stable\/reference\/api\/pandas.DataFrame.html\" target=\"_blank\" rel=\"noopener\">pandas.DataFrame<\/a>\u51fd\u6570\u53ef\u4ee5\u8f7b\u677e\u505a\u5230\u8fd9\u4e00\u70b9\uff0c\u8be5\u51fd\u6570\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\uff1a<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>pandas.DataFrame\uff08\u6570\u636e=\u65e0\uff0c\u7d22\u5f15=\u65e0\uff0c\u5217=\u65e0\uff0c&#8230;\uff09<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u91d1\u5b50\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>data\uff1a<\/strong>\u8981\u8f6c\u6362\u4e3aDataFrame\u7684\u6570\u636e<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>index\uff1a<\/strong>\u7528\u4e8e\u751f\u6210\u7684 DataFrame \u7684\u7d22\u5f15<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>columns\uff1a<\/strong>\u7528\u4e8e\u751f\u6210\u7684 DataFrame \u7684\u5217\u6807\u7b7e<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u672c\u6559\u7a0b\u63d0\u4f9b\u4e86\u8be5\u529f\u80fd\u5b9e\u9645\u4f7f\u7528\u7684\u51e0\u4e2a\u793a\u4f8b\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b 1\uff1a\u5c06\u5217\u8868\u8f6c\u6362\u4e3a DataFrame<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u5c06\u5217\u8868\u8f6c\u6362\u4e3a pandas DataFrame\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create list that contains points scored by 10 basketball players<\/span>\ndata = [4, 14, 17, 22, 26, 29, 33, 35, 35, 38]\n\n<span style=\"color: #008080;\">#convert list to DataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> (data, columns=[' <span style=\"color: #008000;\">points<\/span> '])\n\n<span style=\"color: #008080;\">#view resulting DataFrame<\/span>\n<span style=\"color: #993300;\">print<\/span> (df)\n\n       points\n0 4\n1 14\n2 17\n3 22\n4 26\n5 29\n6 33\n7 35<\/strong><\/pre>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b 2\uff1a\u5c06\u591a\u4e2a\u5217\u8868\u8f6c\u6362\u4e3a DataFrame<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u5c06\u591a\u4e2a\u5217\u8868\u8f6c\u6362\u4e3a pandas DataFrame\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#define lists\n<\/span><span style=\"color: #000000;\">points = [4, 14, 17, 22, 26, 29, 33, 35, 35, 38]\nrebounds = [1, 4, 4, 5, 8, 7, 5, 6, 9, 11]\n\n<span style=\"color: #008080;\">#convert lists into a single list\n<\/span>data = []\ndata. <span style=\"color: #3366ff;\">append<\/span> (dots)\ndata. <span style=\"color: #3366ff;\">append<\/span> (rebounds)\n\n<span style=\"color: #008000;\"><span style=\"color: #008080;\">#view new list<\/span>\n<span style=\"color: #000000;\">data<\/span>\n\n<span style=\"color: #000000;\">[[4, 14, 17, 22, 26, 29, 33, 35, 35, 38], [1, 4, 4, 5, 8, 7, 5, 6, 9, 11]]<\/span>\n<\/span>\n<span style=\"color: #008080;\">#convert list into DataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> (data). <span style=\"color: #3366ff;\">transpose<\/span> ()\ndf. <span style=\"color: #3366ff;\">columns<\/span> =[' <span style=\"color: #008000;\">points<\/span> ', ' <span style=\"color: #008000;\">rebounds<\/span> ']\n\n<span style=\"color: #008080;\">#view resulting DataFrame\n<\/span>df\n\n       rebound points\n0 4 1\n1 14 4\n2 17 4\n3 22 5\n4 26 8\n5 29 7\n6 33 5\n7 35 6\n8 35 9\n9 38 11\n<\/span><\/strong><\/pre>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b 3\uff1a\u5c06\u5217\u8868\u5217\u8868\u8f6c\u6362\u4e3a DataFrame<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u663e\u793a\u4e86\u5982\u4f55\u5c06\u5217\u8868\u5217\u8868\u8f6c\u6362\u4e3a pandas DataFrame\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#define list of lists\n<\/span><span style=\"color: #000000;\">data = [[4, 1], [14, 4], [17, 4], [22, 5], [26, 8],\n        [29, 7], [33, 5], [35, 6], [35, 9], [38,11]]\n\n<span style=\"color: #008080;\">#convert list into DataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> (data, columns=[' <span style=\"color: #008000;\">points<\/span> ', ' <span style=\"color: #008000;\">rebounds<\/span> '])\n\n<span style=\"color: #008080;\">#view resulting DataFrame\n<\/span>df\n\n       rebound points\n0 4 1\n1 14 4\n2 17 4\n3 22 5\n4 26 8\n5 29 7\n6 33 5\n7 35 6\n8 35 9\n9 38 11<\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5feb\u901f\u68c0\u67e5\u751f\u6210\u7684 DataFrame \u4e2d\u7684\u884c\u6570\u548c\u5217\u6570\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #000000;\"><span style=\"color: #107d3f;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#display number of rows and columns in DataFrame<\/span>\ndf.<\/span> <span style=\"color: #3366ff;\">shape\n<\/span><\/span><\/span>\n(10, 2)\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u751f\u6210\u7684 DataFrame \u6709<strong>10<\/strong>\u884c\u548c<strong>2<\/strong>\u5217\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u6765\u68c0\u7d22\u7ed3\u679c DataFrame \u4e2d\u7684\u5217\u540d\u79f0\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #000000;\"><span style=\"color: #008080;\">#display column names of DataFrame<\/span>\nlist(df)\n<\/span>\n['points', 'rebounds']\n<\/strong><\/pre>\n<h3><span style=\"color: #000000;\"><strong>\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u6559\u7a0b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 pandas \u4e2d\u6267\u884c\u5176\u4ed6\u5e38\u89c1\u4efb\u52a1\uff1a<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/cn\/\u7edf\u8ba1\u5b66\u4ee5\u7b80\u5355\u76f4\u63a5\u7684\u65b9\u5f0f\u89e3\u91ca\u6982\u5ff5\uff0c\u6211\u4eec\u4f7f\u5b66\u4e60\u7edf\u8ba1\u53d8\u5f97\u66f4\u5bb9\u6613\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5c06 DataFrame \u8f6c\u6362\u4e3a Pandas \u4e2d\u7684\u5217\u8868<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u7edf\u8ba1\u5b66\u4ee5\u7b80\u5355\u76f4\u63a5\u7684\u65b9\u5f0f\u89e3\u91ca\u6982\u5ff5\uff0c\u6211\u4eec\u4f7f\u5b66\u4e60\u7edf\u8ba1\u53d8\u5f97\u66f4\u5bb9\u6613\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 Pandas \u4e2d\u5c06\u5b57\u5178\u8f6c\u6362\u4e3a DataFrame<\/a><br \/> <a href=\"https:\/\/statorials.org\/cn\/\u5c06\u5b57\u7b26\u4e32\u8f6c\u6362\u4e3a\u6d6e\u52a8\u718a\u732b\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 Pandas \u4e2d\u5c06\u5b57\u7b26\u4e32\u8f6c\u6362\u4e3a\u6d6e\u70b9\u6570<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u901a\u5e38\uff0c\u60a8\u53ef\u80fd\u5e0c\u671b\u5728 Python \u4e2d\u5c06 List \u8f6c\u6362\u4e3a DataFrame\u3002 \u5e78\u8fd0\u7684\u662f\uff0c\u4f7f\u7528pandas.D [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-1518","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u5982\u4f55\u5728 Python \u4e2d\u5c06\u5217\u8868\u8f6c\u6362\u4e3a DataFrame - Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u901a\u8fc7\u51e0\u4e2a\u793a\u4f8b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 Python \u4e2d\u5c06 List \u8f6c\u6362\u4e3a DataFrame\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/cn\/\u5217\u8868\u5230\u6570\u636e\u6846-python\/\" \/>\n<meta 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