<\/p>\n
Ara\u015ft\u0131rmac\u0131lar genellikle bir pop\u00fclasyondan\u00f6rnekler<\/a> al\u0131r ve bu \u00f6rnekteki verileri, bir b\u00fct\u00fcn olarak pop\u00fclasyon hakk\u0131nda sonu\u00e7lar \u00e7\u0131karmak i\u00e7in kullan\u0131r.<\/span><\/p>\n Yayg\u0131n olarak kullan\u0131lan bir \u00f6rnekleme y\u00f6ntemi, iki a\u015famal\u0131 basit bir s\u00fcre\u00e7te uygulanan sistematik \u00f6rneklemedir<\/strong> :<\/span><\/p>\n 1.<\/strong> Bir pop\u00fclasyonun her \u00fcyesini belirli bir s\u0131raya yerle\u015ftirin.<\/span><\/p>\n 2.<\/strong> Rastgele bir ba\u015flang\u0131\u00e7 noktas\u0131 se\u00e7in ve numunenin par\u00e7as\u0131 olacak n \u00fcyeden<\/sup> birini se\u00e7in.<\/span><\/p>\n Bu e\u011fitimde Python’da bir panda DataFrame’inde sistematik \u00f6rneklemenin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r.<\/span><\/p>\n Bir \u00f6\u011fretmenin toplam 500 \u00f6\u011frencisi olan bir okuldan 100 \u00f6\u011frencilik bir \u00f6rneklem elde etmek istedi\u011fini varsayal\u0131m. Her \u00f6\u011frenciyi soyad\u0131na g\u00f6re alfabetik s\u0131raya koydu\u011fu, rastgele bir ba\u015flang\u0131\u00e7 noktas\u0131 se\u00e7ti\u011fi ve her be\u015f \u00f6\u011frenciden birinin \u00f6rneklemde yer ald\u0131\u011f\u0131 sistematik \u00f6rneklemeyi kullanmay\u0131 tercih ediyor.<\/span><\/p>\n A\u015fa\u011f\u0131daki kod Python’da \u00e7al\u0131\u015fmak \u00fczere sahte bir veri \u00e7er\u00e7evesinin nas\u0131l olu\u015fturulaca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, sistematik \u00f6rnekleme yoluyla 100 \u00f6\u011frenciden olu\u015fan bir \u00f6rneklemin nas\u0131l elde edilece\u011fini g\u00f6sterir:<\/span><\/p>\n \u00d6rne\u011fe dahil edilen ilk \u00fcyenin orijinal veri \u00e7er\u00e7evesinin ilk sat\u0131r\u0131nda oldu\u011funu unutmay\u0131n. Numunenin her bir sonraki \u00fcyesi, \u00f6nceki \u00fcyeden 5 sat\u0131r sonra yer al\u0131r.<\/span><\/p>\n Shape()’<\/strong> i kullanarak elde etti\u011fimiz sistematik \u00f6rne\u011fin 100 sat\u0131r ve 2 s\u00fctundan olu\u015fan bir veri \u00e7er\u00e7evesi oldu\u011funu g\u00f6rebiliriz.<\/span><\/p>\n \u00d6rnekleme Y\u00f6ntemi T\u00fcrleri<\/a> Ara\u015ft\u0131rmac\u0131lar genellikle bir pop\u00fclasyondan\u00f6rnekler al\u0131r ve bu \u00f6rnekteki verileri, bir b\u00fct\u00fcn olarak pop\u00fclasyon hakk\u0131nda sonu\u00e7lar \u00e7\u0131karmak i\u00e7in kullan\u0131r. Yayg\u0131n olarak kullan\u0131lan bir \u00f6rnekleme y\u00f6ntemi, iki a\u015famal\u0131 basit bir s\u00fcre\u00e7te uygulanan sistematik \u00f6rneklemedir : 1. Bir pop\u00fclasyonun her \u00fcyesini belirli bir s\u0131raya yerle\u015ftirin. 2. Rastgele bir ba\u015flang\u0131\u00e7 noktas\u0131 se\u00e7in ve numunenin par\u00e7as\u0131 olacak n \u00fcyeden birini […]<\/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-1170","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n \u00d6rnek: pandalar aras\u0131nda sistematik \u00f6rnekleme<\/strong><\/span><\/h2>\n
import<\/span> pandas as<\/span> pd\nimport<\/span> numpy as<\/span> np\nimport<\/span> string\nimport<\/span> random<\/span>\n\n#make this example reproducible<\/span>\nn.p. random<\/span> . seeds<\/span> (0)\n\n#create simple function to generate random last names\n<\/span>def<\/span> randomNames(size=6, chars=string. ascii_uppercase<\/span> ):\n return<\/span> ''. join<\/span> (random. choice<\/span> (chars) for<\/span> _ in<\/span> range(size))\n\n#createDataFrame\n<\/span>df = pd.DataFrame({'last_name': [randomNames() for<\/span> _ in<\/span> range(500)],\n 'GPA': np. random<\/span> . normal<\/span> (loc=85, scale=3, size=500)})\n\n#view first six rows of DataFrame<\/span>\ndf. head<\/span> ()\n\nlast_name GPA\n0 PXGPIV 86.667888\n1 JKRRQI 87.677422\n2 TRIZTC 83.733056\n3 YHUGIN 85.314142\n4 ZVUNVK 85.684160<\/strong><\/pre>\n #obtain systematic sample by selecting every 5th row\n<\/span>sys_sample_df = df. iloc<\/span> [::5]\n\n#view first six rows of DataFrame\n<\/span>sys_sample_df. head<\/span> ()\n\n last_name gpa\n3 ORJFW 88.78065\n8 RWPSB 81.96988\n13 RACZU 79.21433\n18 ZOHKA 80.47246\n23 QJETK 87.09991\n28 JTHWB 83.87300\n\n#view dimensions of data frame\n<\/span>sys_sample_df. shape<\/span>\n\n(100, 2)\n<\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h3>\n
Pandalarda k\u00fcme \u00f6rneklemesi<\/a>
Pandalarda tabakal\u0131 \u00f6rnekleme<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"