<\/p>\n
Birle\u015ftirme \u00f6nleme,<\/strong> bir veri k\u00fcmesindeki, ba\u015fka bir veri k\u00fcmesinde e\u015fle\u015fen de\u011ferlere sahip olmayan t\u00fcm sat\u0131rlar\u0131 d\u00f6nd\u00fcrmenize olanak tan\u0131r.<\/span><\/p>\n \u0130ki panda DataFrames aras\u0131nda birle\u015ftirme \u00f6nleme i\u015flemi ger\u00e7ekle\u015ftirmek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n A\u015fa\u011f\u0131daki iki panda DataFrame’e sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n \u0130kinci DataFrame’de e\u015fle\u015fen bir tak\u0131m bulunmayan ilk DataFrame’deki t\u00fcm sat\u0131rlar\u0131 d\u00f6nd\u00fcrmek i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n \u0130lk DataFrame’den, ikinci DataFrame’de e\u015fle\u015fen bir tak\u0131m ad\u0131na sahip olmayan tam olarak iki tak\u0131m oldu\u011funu g\u00f6rebiliriz.<\/span><\/p>\n Birle\u015fme \u00f6nleme beklendi\u011fi gibi \u00e7al\u0131\u015ft\u0131.<\/span><\/p>\n Sonu\u00e7ta, yaln\u0131zca tak\u0131m ad\u0131n\u0131n ilk DataFrame’e ait oldu\u011fu ancak ikinci DataFrame’e ait olmad\u0131\u011f\u0131 sat\u0131rlar\u0131 i\u00e7eren bir DataFrame elde edilir.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde pandalarda di\u011fer ortak g\u00f6revlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n Pandalarda i\u00e7 birle\u015ftirme nas\u0131l yap\u0131l\u0131r<\/a> Birle\u015ftirme \u00f6nleme, bir veri k\u00fcmesindeki, ba\u015fka bir veri k\u00fcmesinde e\u015fle\u015fen de\u011ferlere sahip olmayan t\u00fcm sat\u0131rlar\u0131 d\u00f6nd\u00fcrmenize olanak tan\u0131r. \u0130ki panda DataFrames aras\u0131nda birle\u015ftirme \u00f6nleme i\u015flemi ger\u00e7ekle\u015ftirmek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabilirsiniz: outer = df1. merge (df2, how=’ outer ‘, indicator= True ) anti_join = outer[(outer._merge==’ left_only ‘)]. drop (‘ _merge ‘, axis= 1 ) A\u015fa\u011f\u0131daki \u00f6rnek, […]<\/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-3436","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n outer = df1. merge<\/span> (df2, how=' outer<\/span> ', indicator= True<\/span> )\n\nanti_join = outer[(outer._merge==' left_only<\/span> ')]. drop<\/span> (' _merge<\/span> ', axis= 1<\/span> )\n<\/strong><\/pre>\n \u00d6rnek: Pandalarda birle\u015ftirme \u00f6nleme i\u015flemi ger\u00e7ekle\u015ftirme<\/strong><\/span><\/h2>\n
import<\/span> pandas as<\/span> pd\n\n#create first DataFrame\n<\/span>df1 = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E'],\n ' points<\/span> ': [18, 22, 19, 14, 30]})\n\nprint<\/span> (df1)\n\n team points\n0 to 18\n1 B 22\n2 C 19\n3 D 14\n4 E 30\n\n#create second DataFrame\n<\/span>df2 = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'F', 'G'],\n ' points<\/span> ': [18, 22, 19, 22, 29]})\n\nprint<\/span> (df2)\n\n team points\n0 to 18\n1 B 22\n2 C 19\n3 F 22\n4 G 29\n<\/strong><\/span><\/pre>\n #perform outer join<\/span>\nouter = df1. merge<\/span> (df2, how=' outer<\/span> ', indicator= True<\/span> )\n\n#perform anti-join\n<\/span>anti_join = outer[(outer._merge==' left_only<\/span> ')]. drop<\/span> (' _merge<\/span> ', axis= 1<\/span> )\n\n#view results\n<\/span>print<\/span> (anti_join)\n\n team points\n3 D 14\n4 E 30<\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
Pandalarda sol birle\u015ftirme nas\u0131l yap\u0131l\u0131r<\/a>
Pandalarda \u00e7apraz birle\u015ftirme nas\u0131l yap\u0131l\u0131r<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"