<\/p>\n
R’deki row-bind’in<\/em> k\u0131saltmas\u0131 olan rbind<\/strong> i\u015flevi, veri \u00e7er\u00e7evelerini sat\u0131rlar\u0131na g\u00f6re birle\u015ftirmek i\u00e7in kullan\u0131labilir.<\/span><\/p>\n Python’da e\u015fde\u011fer i\u015flevi ger\u00e7ekle\u015ftirmek i\u00e7in pandas concat()<\/a> i\u015flevini kullanabiliriz:<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnekler bu fonksiyonun pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6stermektedir.<\/span><\/p>\n A\u015fa\u011f\u0131daki iki panda DataFrame’e sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n Bu iki DataFrame’i sat\u0131rlar\u0131yla h\u0131zl\u0131 bir \u015fekilde birbirine ba\u011flamak i\u00e7in concat()<\/strong> i\u015flevini kullanabiliriz:<\/span><\/p>\n Yeni DataFrame’in indeks de\u011ferlerini s\u0131f\u0131rlamak i\u00e7in reset_index()<\/strong> i\u015flevini de kullanabilece\u011fimizi unutmay\u0131n:<\/span><\/p>\n E\u015fit olmayan say\u0131da s\u00fctuna sahip iki DataFrame’i birbirine ba\u011flamak i\u00e7in concat()<\/strong> i\u015flevini de kullanabiliriz ve eksik de\u011ferler yaln\u0131zca NaN ile doldurulacakt\u0131r:<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde Python’da di\u011fer yayg\u0131n i\u015flevlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n Python’da cbind nas\u0131l kullan\u0131l\u0131r (R’ye e\u015fde\u011fer)<\/a> R’deki row-bind’in k\u0131saltmas\u0131 olan rbind i\u015flevi, veri \u00e7er\u00e7evelerini sat\u0131rlar\u0131na g\u00f6re birle\u015ftirmek i\u00e7in kullan\u0131labilir. Python’da e\u015fde\u011fer i\u015flevi ger\u00e7ekle\u015ftirmek i\u00e7in pandas concat() i\u015flevini kullanabiliriz: df3 = pd. concat ([df1, df2]) A\u015fa\u011f\u0131daki \u00f6rnekler bu fonksiyonun pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6stermektedir. \u00d6rnek 1: Python’da rbind’i e\u015fit s\u00fctunlarla kullan\u0131n A\u015fa\u011f\u0131daki iki panda DataFrame’e sahip oldu\u011fumuzu varsayal\u0131m: import pandas as pd #define […]<\/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-2356","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n df3 = pd. concat<\/span> ([df1, df2])\n<\/strong><\/pre>\n \u00d6rnek 1: Python’da rbind’i e\u015fit s\u00fctunlarla kullan\u0131n<\/strong><\/span><\/h3>\n
import<\/span> pandas as<\/span> pd\n\n#define DataFrames\ndf1 = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E'],\n ' points<\/span> ': [99, 91, 104, 88, 108]})\n\nprint<\/span> (df1)\n\n team points\n0 to 99\n1 B 91\n2 C 104\n3 D 88\n4 E 108\n\ndf2 = pd. DataFrame<\/span> ({' assists<\/span> ': ['F', 'G', 'H', 'I', 'J'],\n ' rebounds<\/span> ': [91, 88, 85, 87, 95]})\n\nprint<\/span> (df2)\n\n team points\n0 F 91\n1 G 88\n2:85\n3 I 87\n4 days 95\n<\/span><\/span><\/strong><\/pre>\n #row-bind two DataFrames\ndf3 = pd. concat<\/span> ([df1, df2])\n\n#view resulting DataFrame\n<\/span>df3\n\n\tteam points\n0 to 99\n1 B 91\n2 C 104\n3 D 88\n4 E 108\n0 F 91\n1 G 88\n2:85\n3 I 87\n4 days 95\n<\/span><\/span><\/strong><\/pre>\n #row-bind two DataFrames and reset index values\ndf3 = pd. concat<\/span> ([df1, df2]). reset_index<\/span> (drop= True<\/span> )\n\n#view resulting DataFrame\n<\/span>df3\n\n\tteam points\n0 to 99\n1 B 91\n2 C 104\n3 D 88\n4 E 108\n5 F 91\n6 G 88\n7:85 a.m.\n8 I 87\n9 D 95<\/span><\/span><\/strong><\/pre>\n \u00d6rnek 2: Python’da E\u015fit Olmayan S\u00fctunlarla rbind Kullan\u0131m\u0131<\/strong><\/span><\/h3>\n
import<\/span> pandas as<\/span> pd\n\n#define DataFrames\ndf1 = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E'],\n ' points<\/span> ': [99, 91, 104, 88, 108]})\n\ndf2 = pd. DataFrame<\/span> ({' team<\/span> ': ['F', 'G', 'H', 'I', 'J'],\n ' points<\/span> ': [91, 88, 85, 87, 95],\n ' rebounds<\/span> ': [24, 27, 27, 30, 35]})<\/span>\n\n#row-bind two DataFrames\ndf3 = pd. concat<\/span> ([df1, df2]). reset_index<\/span> (drop= True<\/span> )\n<\/span>\n#view resulting DataFrame\ndf3\n\n\tteam points rebounds\n0 to 99 NaN\n1 B 91 NaN\n2 C 104 NaN\n3 D 88 NaN\n4 E 108 NaN\n5 F 91 24.0\n6G 88 27.0\n7:85 AM 27.0\n8 I 87 30.0\n9 D 95 35.0<\/span><\/span><\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h3>\n
Pandas’ta D\u00dc\u015eEYARA nas\u0131l yap\u0131l\u0131r<\/a>
Pandalarda belirli bir de\u011fer i\u00e7eren sat\u0131rlar nas\u0131l silinir<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"