<\/p>\n
Bir pandan\u0131n DataFrame’inin bo\u015f olup olmad\u0131\u011f\u0131n\u0131 kontrol etmek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n Bu \u00f6zel s\u00f6zdizimi, DataFrame’deki dizin s\u00fctununun uzunlu\u011funun s\u0131f\u0131r olup olmad\u0131\u011f\u0131n\u0131 kontrol eder; bu, t\u00fcm DataFrame’in bo\u015f olup olmad\u0131\u011f\u0131n\u0131 kontrol etmeye e\u015fde\u011ferdir.<\/span><\/p>\n DataFrame bo\u015fsa bu s\u00f6zdizimi True de\u011ferini<\/strong> d\u00f6nd\u00fcr\u00fcr. Aksi takdirde False de\u011ferini<\/strong> d\u00f6nd\u00fcr\u00fcr.<\/span><\/p>\n DataFrame’in bo\u015f olup olmad\u0131\u011f\u0131n\u0131 bildiren \u00f6zel metni yazd\u0131rmak istiyorsan\u0131z basit bir if else<\/strong> i\u015flevini kullanabilirsiniz:<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnekte bu fonksiyonlar\u0131n pratikte nas\u0131l kullan\u0131laca\u011f\u0131 g\u00f6sterilmektedir.<\/span><\/p>\n A\u015fa\u011f\u0131daki bo\u015f pandalara sahip oldu\u011fumuzu varsayal\u0131m DataFrame:<\/span><\/p>\n Pandalar\u0131n DataFrame’inin bo\u015f olup olmad\u0131\u011f\u0131n\u0131 kontrol etmek i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n \u0130\u015flev True<\/strong> de\u011ferini d\u00f6nd\u00fcr\u00fcr ve bu bize DataFrame’in ger\u00e7ekten bo\u015f oldu\u011funu s\u00f6yler.<\/span><\/span><\/p>\n DataFrame’in bo\u015f olup olmad\u0131\u011f\u0131n\u0131 bize bildiren \u00f6zel metni yazd\u0131rmak i\u00e7in a\u015fa\u011f\u0131daki kodu da kullanabiliriz:<\/span><\/p>\n \u00c7\u0131kt\u0131 bize DataFrame’in bo\u015f oldu\u011funu s\u00f6yler.<\/span><\/p>\n \u00d6te yandan, bo\u015f olmayan bir DataFrame’imiz oldu\u011funu varsayal\u0131m:<\/span><\/p>\n DataFrame’in bo\u015f olup olmad\u0131\u011f\u0131n\u0131 kontrol etmek i\u00e7in len()<\/strong> i\u015flevini kullanabiliriz:<\/span><\/p>\n \u0130\u015flev, DataFrame’in bo\u015f olmad\u0131\u011f\u0131n\u0131 bize bildiren False de\u011ferini<\/strong> d\u00f6nd\u00fcr\u00fcr.<\/span><\/p>\n Ve if else<\/strong> i\u015flevini kullan\u0131rsak \u00f6zel \u00e7\u0131kt\u0131 d\u00f6nd\u00fcrebiliriz:<\/span><\/p>\n \u00c7\u0131kt\u0131 bize DataFrame’in bo\u015f olmad\u0131\u011f\u0131n\u0131 s\u00f6yler.<\/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 Pandas DataFrame’de h\u00fccrenin bo\u015f olup olmad\u0131\u011f\u0131 nas\u0131l kontrol edilir<\/a> Bir pandan\u0131n DataFrame’inin bo\u015f olup olmad\u0131\u011f\u0131n\u0131 kontrol etmek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabilirsiniz: len ( df.index ) == 0 Bu \u00f6zel s\u00f6zdizimi, DataFrame’deki dizin s\u00fctununun uzunlu\u011funun s\u0131f\u0131r olup olmad\u0131\u011f\u0131n\u0131 kontrol eder; bu, t\u00fcm DataFrame’in bo\u015f olup olmad\u0131\u011f\u0131n\u0131 kontrol etmeye e\u015fde\u011ferdir. DataFrame bo\u015fsa bu s\u00f6zdizimi True de\u011ferini d\u00f6nd\u00fcr\u00fcr. Aksi takdirde False de\u011ferini d\u00f6nd\u00fcr\u00fcr. DataFrame’in bo\u015f olup olmad\u0131\u011f\u0131n\u0131 […]<\/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-4137","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n len<\/span> ( df.index<\/span> ) ==<\/span> 0\n<\/span><\/strong><\/pre>\n if<\/span> len<\/span> ( df.index<\/span> ) ==<\/span> 0<\/span> :\n print<\/span> (' df is empty<\/span> ')\nelse<\/span> :\n print<\/span> (' df is not empty<\/span> ')<\/strong><\/span><\/pre>\n \u00d6rnek: Pandas DataFrame’in bo\u015f olup olmad\u0131\u011f\u0131n\u0131 kontrol edin<\/strong><\/span><\/h2>\n
import<\/span> pandas as<\/span> pd\n\n#create empty DataFrame\n<\/span>df = pd. DataFrame<\/span> (columns=[' A<\/span> ',' B<\/span> ',' C<\/span> ',' D<\/span> ',' E<\/span> '])\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\nEmpty DataFrame\nColumns: [A, B, C, D, E]\nIndex: []<\/span><\/strong><\/pre>\n #check if DataFrame is empty<\/span>\nlen<\/span> ( df.index<\/span> ) ==<\/span> 0\n\nTrue<\/span><\/span><\/strong><\/pre>\n #check if DataFrame is empty and return output<\/span>\nif<\/span> len<\/span> ( df.index<\/span> ) ==<\/span> 0<\/span> :\n print<\/span> (' df is empty<\/span> ')\nelse<\/span> :\n print<\/span> (' df is not empty<\/span> ')\n\ndf is empty\n<\/strong><\/span><\/pre>\n import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df_full = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n ' points<\/span> ': [18, 22, 19, 14, 14, 11, 20, 28],\n ' assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n ' rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n#view DataFrame\n<\/span>print<\/span> (df_full)\n\n team points assists rebounds\n0 A 18 5 11\n1 B 22 7 8\n2 C 19 7 10\n3 D 14 9 6\n4 E 14 12 6\n5 F 11 9 5\n6 G 20 9 9\n7:28 4 12\n<\/span><\/strong><\/pre>\n #check if DataFrame is empty<\/span>\nlen<\/span> ( df_full.index<\/span> ) ==<\/span> 0\n\nFalse<\/span><\/span><\/strong><\/pre>\n #check if DataFrame is empty and return output<\/span>\nif<\/span> len<\/span> ( df_full.index<\/span> ) ==<\/span> 0<\/span> :\n print<\/span> (' df is empty<\/span> ')\nelse<\/span> :\n print<\/span> (' df is not empty<\/span> ')\n\ndf is not empty\n<\/strong><\/span><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
Pandas DataFrame’de bir h\u00fccrenin de\u011feri nas\u0131l elde edilir<\/a>
S\u00fctun adlar\u0131yla bo\u015f bir Pandas DataFrame nas\u0131l olu\u015fturulur<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"