{"id":1555,"date":"2023-07-25T22:07:10","date_gmt":"2023-07-25T22:07:10","guid":{"rendered":"https:\/\/statorials.org\/tr\/pythonda-ondalik-sayilar\/"},"modified":"2023-07-25T22:07:10","modified_gmt":"2023-07-25T22:07:10","slug":"pythonda-ondalik-sayilar","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/pythonda-ondalik-sayilar\/","title":{"rendered":"Python&#39;da ondal\u0131k say\u0131 nas\u0131l hesaplan\u0131r: \u00f6rneklerle"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0130statistikte <strong>ondal\u0131k<\/strong> say\u0131lar, bir veri k\u00fcmesini e\u015fit frekansta on gruba b\u00f6len say\u0131lard\u0131r.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0130lk ondal\u0131k dilim, t\u00fcm veri de\u011ferlerinin %10\u2019unun alt\u0131na d\u00fc\u015ft\u00fc\u011f\u00fc noktad\u0131r. \u0130kinci ondal\u0131k dilim, t\u00fcm veri de\u011ferlerinin %20&#8217;sinin alt\u0131na d\u00fc\u015ft\u00fc\u011f\u00fc noktad\u0131r ve bu b\u00f6yle devam eder.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Python&#8217;da bir veri k\u00fcmesinin ondal\u0131k dilimlerini hesaplamak i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabiliriz:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n\nn.p. <span style=\"color: #3366ff;\">percentile<\/span> (var, np. <span style=\"color: #3366ff;\">arange<\/span> (0, 100, 10))\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">A\u015fa\u011f\u0131daki \u00f6rnekte bu fonksiyonun pratikte nas\u0131l kullan\u0131laca\u011f\u0131 g\u00f6sterilmektedir.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u00d6rnek: Python&#8217;da ondal\u0131k say\u0131lar\u0131 hesaplama<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">A\u015fa\u011f\u0131daki kod, 20 de\u011fere sahip sahte bir veri k\u00fcmesinin nas\u0131l olu\u015fturulaca\u011f\u0131n\u0131 ve ard\u0131ndan veri k\u00fcmesinin ondal\u0131k de\u011ferlerinin nas\u0131l hesaplanaca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n\n<span style=\"color: #008080;\">#createdata\n<\/span>data = np. <span style=\"color: #3366ff;\">array<\/span> ([56, 58, 64, 67, 68, 73, 78, 83, 84, 88,\n                 89, 90, 91, 92, 93, 93, 94, 95, 97, 99])\n\n<span style=\"color: #008080;\">#calculate deciles of data\n<\/span>n.p. <span style=\"color: #3366ff;\">percentile<\/span> (data, np. <span style=\"color: #3366ff;\">arange<\/span> (0, 100, 10))\n\narray([56., 63.4, 67.8, 76.5, 83.6, 88.5, 90.4, 92.3, 93.2, 95.2])<\/strong><\/span><\/pre>\n<p> <span style=\"color: #000000;\">Ondal\u0131k say\u0131lar\u0131 yorumlaman\u0131n yolu a\u015fa\u011f\u0131daki gibidir:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">T\u00fcm veri de\u011ferlerinin %10&#8217;u <strong>63,4&#8217;ten<\/strong> azd\u0131r<\/span><\/li>\n<li> <span style=\"color: #000000;\">T\u00fcm veri de\u011ferlerinin %20&#8217;si <strong>67,8&#8217;den<\/strong> k\u00fc\u00e7\u00fckt\u00fcr.<\/span><\/li>\n<li> <span style=\"color: #000000;\">T\u00fcm veri de\u011ferlerinin %30&#8217;u <strong>76,5&#8217;tan<\/strong> k\u00fc\u00e7\u00fckt\u00fcr.<\/span><\/li>\n<li> <span style=\"color: #000000;\">T\u00fcm veri de\u011ferlerinin %40&#8217;\u0131 <strong>83,6&#8217;dan<\/strong> k\u00fc\u00e7\u00fckt\u00fcr.<\/span><\/li>\n<li> <span style=\"color: #000000;\">T\u00fcm veri de\u011ferlerinin %50&#8217;si <strong>88,5&#8217;ten<\/strong> k\u00fc\u00e7\u00fckt\u00fcr.<\/span><\/li>\n<li> <span style=\"color: #000000;\">T\u00fcm veri de\u011ferlerinin %60&#8217;\u0131 <strong>90,4&#8217;ten<\/strong> k\u00fc\u00e7\u00fckt\u00fcr.<\/span><\/li>\n<li> <span style=\"color: #000000;\">T\u00fcm veri de\u011ferlerinin %70&#8217;i <strong>92,3&#8217;ten<\/strong> k\u00fc\u00e7\u00fckt\u00fcr.<\/span><\/li>\n<li> <span style=\"color: #000000;\">T\u00fcm veri de\u011ferlerinin %80&#8217;i <strong>93,2&#8217;den<\/strong> k\u00fc\u00e7\u00fckt\u00fcr.<\/span><\/li>\n<li> <span style=\"color: #000000;\">T\u00fcm veri de\u011ferlerinin %90&#8217;\u0131 <strong>95,2&#8217;den<\/strong> k\u00fc\u00e7\u00fckt\u00fcr.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\"><span style=\"color: #000000;\">\u00c7\u0131k\u0131\u015f\u0131n (56) ilk de\u011ferinin basit\u00e7e veri setinin minimum de\u011ferini g\u00f6sterdi\u011fine dikkat edin.<\/span><\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u00d6rnek: Python&#8217;da De\u011ferleri Ondal\u0131k Say\u0131ya Yerle\u015ftirme<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Her veri de\u011ferini ondal\u0131k dilime yerle\u015ftirmek i\u00e7in pandas <strong>qcut<\/strong> fonksiyonunu kullanabiliriz.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u00d6nceki \u00f6rnekte olu\u015fturdu\u011fumuz veri k\u00fcmesi i\u00e7in bu i\u015flevin nas\u0131l kullan\u0131laca\u011f\u0131 a\u015fa\u011f\u0131da a\u00e7\u0131klanm\u0131\u015ft\u0131r:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #993300;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create data frame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">values<\/span> ': [56, 58, 64, 67, 68, 73, 78, 83, 84, 88,\n                              89, 90, 91, 92, 93, 93, 94, 95, 97, 99]})\n\n<span style=\"color: #008080;\">#calculate decile of each value in data frame\n<\/span>df[' <span style=\"color: #ff0000;\">Decile<\/span> '] = pd. <span style=\"color: #3366ff;\">qcut<\/span> (df[' <span style=\"color: #ff0000;\">values<\/span> '], 10, labels= <span style=\"color: #008000;\">False<\/span> )\n\n<span style=\"color: #008080;\">#display data frame\n<\/span>df\n\n\tvalues Decile\n0 56 0\n1 58 0\n2 64 1\n3 67 1\n4 68 2\n5 73 2\n6 78 3\n7 83 3\n8 84 4\n9 88 4\n10 89 5\n11 90 5\n12 91 6\n13 92 6\n14 93 7\n15 93 7\n16 94 8\n17 95 8\n18 97 9\n19 99 9<\/span>\n<\/span><\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Sonucun yorumlanma \u015fekli \u015fu \u015fekildedir:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">Veri de\u011feri 56, y\u00fczdelik dilim %0 ile %10 aras\u0131nda oldu\u011fundan ondal\u0131k dilim <strong>0&#8217;dad\u0131r<\/strong> .<\/span><\/li>\n<li> <span style=\"color: #000000;\">Veri de\u011feri 58, y\u00fczdelik dilim %0 ile %10 aras\u0131nda oldu\u011fundan ondal\u0131k dilim <strong>0&#8217;dad\u0131r<\/strong> .<\/span><\/li>\n<li> <span style=\"color: #000000;\">Veri de\u011feri (64) %10 ila %20 y\u00fczdelik dilim aras\u0131ndad\u0131r, yani ondal\u0131k <strong>1&#8217;dedir<\/strong> .<\/span><\/li>\n<li> <span style=\"color: #000000;\">Veri de\u011feri 67, %10 ile %20 y\u00fczdelik dilim aras\u0131nda yer al\u0131r, dolay\u0131s\u0131yla ondal\u0131k <strong>1&#8217;e<\/strong> d\u00fc\u015fer.<\/span><\/li>\n<li> <span style=\"color: #000000;\">Veri de\u011feri 68, %20 ila %30 y\u00fczdelik dilim aras\u0131nda yer al\u0131r, dolay\u0131s\u0131yla ondal\u0131k <strong>2&#8217;ye<\/strong> d\u00fc\u015fer.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">Ve benzeri.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Ek kaynaklar<\/strong><\/span><\/h3>\n<p> <a href=\"https:\/\/statorials.org\/tr\/pythonda-yuzdelikler\/\" target=\"_blank\" rel=\"noopener\">Python&#8217;da y\u00fczdelikler nas\u0131l hesaplan\u0131r<\/a><br \/> <a href=\"https:\/\/statorials.org\/tr\/python-ceyrekler-arasi-aralik\/\" target=\"_blank\" rel=\"noopener\">Python&#8217;da \u00e7eyrekler aras\u0131 aral\u0131k nas\u0131l hesaplan\u0131r<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0130statistikte ondal\u0131k say\u0131lar, bir veri k\u00fcmesini e\u015fit frekansta on gruba b\u00f6len say\u0131lard\u0131r. \u0130lk ondal\u0131k dilim, t\u00fcm veri de\u011ferlerinin %10\u2019unun alt\u0131na d\u00fc\u015ft\u00fc\u011f\u00fc noktad\u0131r. \u0130kinci ondal\u0131k dilim, t\u00fcm veri de\u011ferlerinin %20&#8217;sinin alt\u0131na d\u00fc\u015ft\u00fc\u011f\u00fc noktad\u0131r ve bu b\u00f6yle devam eder. Python&#8217;da bir veri k\u00fcmesinin ondal\u0131k dilimlerini hesaplamak i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabiliriz: import numpy as np n.p. percentile (var, [&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-1555","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Python&#039;da Ondal\u0131k Say\u0131 Nas\u0131l Hesaplan\u0131r: \u00d6rneklerle<\/title>\n<meta name=\"description\" content=\"Bu e\u011fitimde Python&#039;da ondal\u0131k say\u0131lar\u0131n nas\u0131l hesaplanaca\u011f\u0131 birka\u00e7 \u00f6rnekle a\u00e7\u0131klanmaktad\u0131r.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, 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