<\/p>\n
Python’da kar\u015f\u0131la\u015fabilece\u011finiz bir hata:<\/span><\/p>\n Bu hata genellikle bir pandan\u0131n DataFrame’ini &<\/strong> ve |<\/strong> karakterlerini kullanmak yerine ve<\/strong> ve veya<\/strong> s\u00f6zc\u00fcklerini kullanarak filtrelemeye \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131zda ortaya \u00e7\u0131kar. operat\u00f6rler.<\/span><\/p>\n Bu e\u011fitimde bu hatan\u0131n pratikte nas\u0131l \u00e7\u00f6z\u00fclece\u011fi a\u00e7\u0131klanmaktad\u0131r.<\/span><\/p>\n A\u015fa\u011f\u0131daki pandalar\u0131 DataFrame olu\u015fturdu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n \u015eimdi tak\u0131m\u0131n “A”ya e\u015fit oldu\u011fu ve<\/strong> puanlar\u0131n 20’den az oldu\u011fu sat\u0131rlar\u0131 filtrelemeye \u00e7al\u0131\u015ft\u0131\u011f\u0131m\u0131z\u0131 varsayal\u0131m:<\/span><\/p>\n Veya tak\u0131m\u0131n “A”ya e\u015fit oldu\u011fu veya<\/b> puanlar\u0131n 20’den az oldu\u011fu sat\u0131rlar\u0131 filtrelemeye \u00e7al\u0131\u015ft\u0131\u011f\u0131m\u0131z\u0131 varsayal\u0131m:<\/span><\/p>\n Her iki senaryoda da bir serinin do\u011fruluk de\u011ferinin belirsiz oldu\u011funu s\u00f6yleyen bir hata al\u0131r\u0131z.<\/span><\/p>\n Filtreleme yaparken bu hatay\u0131 \u00f6nlemek i\u00e7in &<\/strong> ve |<\/strong> karakterlerini kulland\u0131\u011f\u0131m\u0131zdan emin olmam\u0131z gerekir. elementler. operat\u00f6rler.<\/span><\/p>\n \u00d6rne\u011fin tak\u0131m\u0131n “A”ya e\u015fit oldu\u011fu ve<\/strong> puanlar\u0131n 20’den az oldu\u011fu sat\u0131rlar\u0131 filtrelemek i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n Veya tak\u0131m\u0131n “A”ya e\u015fit oldu\u011fu veya<\/b> puanlar\u0131n 20’den az oldu\u011fu sat\u0131rlar\u0131 filtrelemek i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n Her iki senaryoda da &<\/strong> ve |<\/strong> karakterlerini kulland\u0131\u011f\u0131m\u0131z i\u00e7in hata alm\u0131yoruz. elementler. operat\u00f6rler.<\/span><\/p>\n Not<\/strong> : Bir pandan\u0131n DataFrame’ini birden \u00e7ok ko\u015fula g\u00f6re filtrelerken her bir ko\u015fulun etraf\u0131na parantez eklemek \u00f6nemlidir, aksi halde bir hata al\u0131rs\u0131n\u0131z.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde Python’daki di\u011fer yayg\u0131n hatalar\u0131n nas\u0131l d\u00fczeltilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n Nas\u0131l d\u00fczeltilir: “pandalar” mod\u00fcl\u00fcnde “dataframe” \u00f6zelli\u011fi yok<\/a> Python’da kar\u015f\u0131la\u015fabilece\u011finiz bir hata: ValueError : The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all(). Bu hata genellikle bir pandan\u0131n DataFrame’ini & ve | karakterlerini kullanmak yerine ve ve veya s\u00f6zc\u00fcklerini kullanarak filtrelemeye \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131zda ortaya \u00e7\u0131kar. operat\u00f6rler. Bu e\u011fitimde bu hatan\u0131n pratikte nas\u0131l \u00e7\u00f6z\u00fclece\u011fi a\u00e7\u0131klanmaktad\u0131r. Hata nas\u0131l yeniden olu\u015fturulur? […]<\/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-3195","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n ValueError<\/span> : The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(),\n a.any() or a.all().\n<\/strong><\/pre>\n Hata nas\u0131l yeniden olu\u015fturulur?<\/strong><\/h3>\n
import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],\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)\n\n team points assists rebounds\n0 A 18 5 11\n1 to 22 7 8\n2 A 19 7 10\n3 A 14 9 6\n4 B 14 12 6\n5 B 11 9 5\n6 B 20 9 9\n7 B 28 4 12\n<\/strong><\/span><\/pre>\n #attempt to filter DataFrame\n<\/span>df[(df[' team<\/span> '] == ' A<\/span> ') and<\/span> (df[' points<\/span> '] < 20<\/span> )]\n\nValueError<\/span> : The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(),\n a.any() or a.all().\n<\/strong><\/span><\/pre>\n #attempt to filter DataFrame\n<\/span>df[(df['<\/span> team<\/span> '] == '<\/span> A<\/span> ')<\/span> or<\/span> (df['<\/span> points<\/span> '] <<\/span> 20<\/span> )]\n\n<\/span>ValueError<\/span> : The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(),\n a.any() or a.all().<\/span><\/strong><\/span><\/pre>\n Hata nas\u0131l d\u00fczeltilir?<\/strong><\/h3>\n
#filter DataFrame\n<\/span>df[(df['<\/span> team<\/span> '] == '<\/span> A<\/span> ')<\/span> &<\/span> (df['<\/span> points<\/span> '] <<\/span> 20<\/span> )]\n\n<\/span>team points assists rebounds\n0 A 18 5 11\n2 A 19 7 10\n3 A 14 9 6<\/span><\/strong><\/span><\/pre>\n #filter DataFrame\n<\/span>df[(df[' team<\/span> '] == ' A<\/span> ') |<\/span> (df[' points<\/span> '] < 20<\/span> )]\n\n team points assists rebounds\n0 A 18 5 11\n1 to 22 7 8\n2 A 19 7 10\n3 A 14 9 6\n4 B 14 12 6\n5 B 11 9 5<\/strong><\/span><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h3>\n
Pandalar’da nas\u0131l d\u00fczeltilir: SettingWithCopyWarning<\/a>
Pandalarda Nas\u0131l D\u00fczeltilir: TypeError: \u00c7izilecek say\u0131sal veri yok<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"