<\/p>\n
Pandalar\u0131 kullan\u0131rken kar\u015f\u0131la\u015fabilece\u011finiz bir hata:<\/span><\/p>\n Bu hata, pandas DataFrame’deki bir s\u00fctunu kayan de\u011ferden tam say\u0131ya d\u00f6n\u00fc\u015ft\u00fcrmeye \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131zda, s\u00fctun NaN de\u011ferleri i\u00e7erdi\u011finde ortaya \u00e7\u0131kar.<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnekte bu hatan\u0131n pratikte nas\u0131l d\u00fczeltilece\u011fi g\u00f6sterilmektedir.<\/span><\/p>\n A\u015fa\u011f\u0131daki pandalar\u0131 DataFrame olu\u015fturdu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n \u015eu anda “geri d\u00f6nenler” s\u00fctunu “float” veri t\u00fcr\u00fcndedir.<\/span><\/p>\n “Hemen d\u00f6nenler” s\u00fctununu kayan de\u011ferden tam say\u0131ya d\u00f6n\u00fc\u015ft\u00fcrmeye \u00e7al\u0131\u015ft\u0131\u011f\u0131m\u0131z\u0131 varsayal\u0131m:<\/span><\/p>\n “Bounces” s\u00fctunundaki NaN de\u011ferleri tam say\u0131 de\u011ferlerine d\u00f6n\u00fc\u015ft\u00fcr\u00fclemedi\u011fi i\u00e7in ValueError<\/strong> al\u0131yoruz.<\/span><\/p>\n Bu hatay\u0131 d\u00fczeltmenin yolu, s\u00fctunu kayan noktal\u0131 durumdan tam say\u0131ya d\u00f6n\u00fc\u015ft\u00fcrmeye \u00e7al\u0131\u015fmadan \u00f6nce NaN de\u011ferlerini i\u015flemektir.<\/span><\/p>\n \u00d6ncelikle NaN de\u011ferleri i\u00e7eren sat\u0131rlar\u0131 tan\u0131mlamak i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n Daha sonra, s\u00fctunu kayan noktal\u0131 durumdan tam say\u0131ya d\u00f6n\u00fc\u015ft\u00fcrmeden \u00f6nce NaN de\u011ferlerine sahip sat\u0131rlar\u0131 kald\u0131rabilir veya NaN de\u011ferlerini ba\u015fka bir de\u011ferle de\u011fi\u015ftirebiliriz:<\/span><\/p>\n Y\u00f6ntem 1: NaN de\u011ferlerine sahip sat\u0131rlar\u0131 kald\u0131r\u0131n<\/strong><\/span><\/p>\n Y\u00f6ntem 2: NaN De\u011ferlerini De\u011fi\u015ftirin<\/strong><\/span><\/p>\n Her iki y\u00f6ntemin de ValueError’dan<\/strong> ka\u00e7\u0131nmam\u0131za ve kayan noktal\u0131 s\u00fctunu ba\u015far\u0131yla bir tamsay\u0131 s\u00fctununa d\u00f6n\u00fc\u015ft\u00fcrmemize olanak sa\u011flad\u0131\u011f\u0131n\u0131 unutmay\u0131n.<\/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? S\u00fctunlar \u00e7ak\u0131\u015f\u0131yor ancak son ek belirtilmemi\u015f<\/a> Pandalar\u0131 kullan\u0131rken kar\u015f\u0131la\u015fabilece\u011finiz bir hata: ValueError : cannot convert float NaN to integer Bu hata, pandas DataFrame’deki bir s\u00fctunu kayan de\u011ferden tam say\u0131ya d\u00f6n\u00fc\u015ft\u00fcrmeye \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131zda, s\u00fctun NaN de\u011ferleri i\u00e7erdi\u011finde ortaya \u00e7\u0131kar. A\u015fa\u011f\u0131daki \u00f6rnekte bu hatan\u0131n pratikte nas\u0131l d\u00fczeltilece\u011fi g\u00f6sterilmektedir. Hata nas\u0131l yeniden olu\u015fturulur? A\u015fa\u011f\u0131daki pandalar\u0131 DataFrame olu\u015fturdu\u011fumuzu varsayal\u0131m: import pandas as pd import numpy as […]<\/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-2113","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n ValueError<\/span> : cannot convert float NaN to integer\n<\/strong><\/pre>\n Hata nas\u0131l yeniden olu\u015fturulur?<\/strong><\/span><\/h3>\n
import<\/span> pandas as<\/span> pd\nimport<\/span> numpy as<\/span> np\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' points<\/span> ': [25, 12, 15, 14, 19, 23, 25, 29],\n ' assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n ' rebounds<\/span> ': [11, np. no<\/span> , 10, 6, 5, np. no<\/span> , 9, 12]})\n\n#view DataFrame\n<\/span>df\n\n points assists rebounds\n0 25 5 11\n1 12 7 NaN\n2 15 7 10\n3 14 9 6\n4 19 12 5\n5 23 9 NaN\n6 25 9 9\n7 29 4 12<\/strong><\/pre>\n #print data type of 'rebounds' column\n<\/span>df[' rebounds<\/span> ']. dtype\n\ndtype('float64')\n<\/span><\/span><\/strong><\/pre>\n #attempt to convert 'rebounds' column from float to integer<\/span>\ndf[' rebounds<\/span> '] = df[' rebounds<\/span> ']. astype<\/span> (int)\n\nValueError<\/span> : cannot convert float NaN to integer \n<\/strong><\/pre>\n Hata nas\u0131l d\u00fczeltilir?<\/strong><\/span><\/h3>\n
#print rows in DataFrame that contain NaN in 'rebounds' column\n<\/span>print<\/span> (df[df[' rebounds<\/span> ']. isnull<\/span> ()])\n\n points assists rebounds\n1 12 7 NaN\n5 23 9 NaN\n<\/strong><\/pre>\n #drop all rows with NaN values\n<\/span>df = df. dropna<\/span> ()\n\n#convert 'rebounds' column from float to integer<\/span>\ndf[' rebounds<\/span> '] = df[' rebounds<\/span> ']. astype<\/span> (int) \n\n#view updated DataFrame\n<\/span>df\n\tpoints assists rebounds\n0 25 5 11\n2 15 7 10\n3 14 9 6\n4 19 12 5\n6 25 9 9\n7 29 4 12\n\n#view class of 'rebounds' column<\/span>\ndf[' rebounds<\/span> ']. dtype\n\ndtype('int64')<\/span><\/span>\n<\/span><\/strong><\/pre>\n #replace all NaN values with zeros\n<\/span>df[' rebounds<\/span> '] = df[' rebounds<\/span> ']. fillna<\/span> ( 0<\/span> )\n\n#convert 'rebounds' column from float to integer<\/span>\ndf[' rebounds<\/span> '] = df[' rebounds<\/span> ']. astype<\/span> (int) \n\n#view updated DataFrame\n<\/span>df\n\n\tpoints assists rebounds\n0 25 5 11\n1 12 7 0\n2 15 7 10\n3 14 9 6\n4 19 12 5\n5 23 9 0\n6 25 9 9\n7 29 4 12\n\n#view class of 'rebounds' column<\/span>\ndf[' rebounds<\/span> ']. dtype\n\ndtype('int64')<\/span><\/span><\/span><\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h3>\n
Nas\u0131l d\u00fczeltilir: ‘numpy.ndarray’ nesnesinin ‘append’ \u00f6zelli\u011fi yok<\/a>
Nas\u0131l d\u00fczeltilir? T\u00fcm skaler de\u011ferleri kullan\u0131yorsan\u0131z bir dizin iletmeniz gerekir<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"