<\/p>\n
Bir pandas DataFrame’de ko\u015fula dayal\u0131 bir Boole s\u00fctunu olu\u015fturmak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n Bu \u00f6zel s\u00f6zdizimi, iki olas\u0131 de\u011fere sahip yeni bir Boolean s\u00fctunu olu\u015fturur:<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n \u00c7e\u015fitli basketbol oyuncular\u0131 hakk\u0131nda bilgi i\u00e7eren a\u015fa\u011f\u0131daki pandalar DataFrame’e sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n Puan s\u00fctunundaki de\u011fer 15’ten b\u00fcy\u00fckse True<\/strong> , aksi takdirde False<\/strong> de\u011ferini d\u00f6nd\u00fcren good_player<\/strong> ad\u0131nda yeni bir s\u00fctun olu\u015fturmak i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n good_player<\/strong> adl\u0131 yeni s\u00fctunun yaln\u0131zca iki de\u011fer i\u00e7erdi\u011fini unutmay\u0131n: True<\/strong> veya False<\/strong> .<\/span><\/p>\n Yeni good_player<\/strong> s\u00fctununun ger\u00e7ekten bir Boolean s\u00fctunu oldu\u011funu do\u011frulamak i\u00e7in dtypes()<\/strong> i\u015flevini kullanabiliriz:<\/span><\/p>\n Yeni good_player<\/strong> s\u00fctunu asl\u0131nda bir Boolean s\u00fctunudur.<\/span><\/p>\n Ayr\u0131ca isterseniz Do\u011fru<\/strong> ve Yanl\u0131\u015f<\/strong> yerine 1<\/strong> ve 0<\/strong> gibi say\u0131sal de\u011ferleri de d\u00f6nd\u00fcrebilece\u011finizi unutmay\u0131n:<\/span><\/p>\n Puan<\/strong> s\u00fctunundaki kar\u015f\u0131l\u0131k gelen de\u011fer 15’ten b\u00fcy\u00fckse good_player<\/strong> s\u00fctunu art\u0131k 1<\/strong> de\u011ferini i\u00e7erir.<\/span><\/p>\n Aksi takdirde 0<\/strong> de\u011ferini i\u00e7erir.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde pandalarda di\u011fer yayg\u0131n i\u015flemlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n Pandalar’da birden \u00e7ok ko\u015fula g\u00f6re sat\u0131rlar nas\u0131l se\u00e7ilir<\/a> Bir pandas DataFrame’de ko\u015fula dayal\u0131 bir Boole s\u00fctunu olu\u015fturmak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz: df[‘ boolean_column ‘] = np. where (df[‘ some_column ‘] > 15, True , False ) Bu \u00f6zel s\u00f6zdizimi, iki olas\u0131 de\u011fere sahip yeni bir Boolean s\u00fctunu olu\u015fturur: Some_column’daki de\u011fer 15’ten b\u00fcy\u00fckse do\u011frudur . Baz\u0131_s\u00fctunlardaki de\u011fer 15’ten k\u00fc\u00e7\u00fck veya ona e\u015fitse false […]<\/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-3699","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n df[' boolean_column<\/span> '] = np. where<\/span> (df[' some_column<\/span> '] > 15, True<\/span> , False<\/span> )\n<\/strong><\/pre>\n\n
\u00d6rnek: Pandalarda Ko\u015fula G\u00f6re Boole S\u00fctunu Olu\u015fturma<\/strong><\/span><\/h2>\n
import<\/span> pandas as<\/span> pd\n\n#createDataFrame\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],\n ' points<\/span> ': [5, 17, 7, 19, 12, 13, 9, 24]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n team points\n0 to 5\n1 to 17\n2 to 7\n3 to 19\n4 B 12\n5 B 13\n6 B 9\n7 B 24 \n<\/span><\/span><\/strong><\/pre>\n import<\/span> numpy as<\/span> np\n\n#create new boolean column based on value in points column\n<\/span>df[' good_player<\/span> '] = np. where<\/span> (df[' points<\/span> '] > 15, True<\/span> , False<\/span> )\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n team points good_player\n0 To 5 False\n1 To 17 True\n2 To 7 False\n3 To 19 True\n4 B 12 False\n5 B 13 False\n6 B 9 False\n7 B 24 True<\/span><\/span><\/strong><\/pre>\n #display data type of good_player column<\/span>\n<\/span>df[' good_player<\/span> ']. dtype\n\n<\/span>dtype('bool')\n<\/span><\/span><\/strong><\/pre>\n import<\/span> numpy as<\/span> np\n\n#create new boolean column based on value in points column\n<\/span>df[' good_player<\/span> '] = np. where<\/span> (df[' points<\/span> '] > 15, 1<\/span> ,<\/span> 0<\/span> )\n\n#view updated DataFrame\n<\/span><\/span>print<\/span> (df)\n\n team points good_player\n0 to 5 0\n1 To 17 1\n2 to 7 0\n3 A 19 1\n4 B 12 0\n5 B 13 0\n6 B 9 0\n7 B 24 1\n<\/span><\/span><\/span><\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
Pandalar’da bir ko\u015fula dayal\u0131 yeni bir s\u00fctun nas\u0131l olu\u015fturulur?<\/a>
Pandas DataFrame’i birden \u00e7ok ko\u015fulda filtreleme<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"