{"id":4084,"date":"2023-07-13T17:18:47","date_gmt":"2023-07-13T17:18:47","guid":{"rendered":"https:\/\/statorials.org\/tr\/pandalar-csvyi-farkli-sayida-sutunla-okur\/"},"modified":"2023-07-13T17:18:47","modified_gmt":"2023-07-13T17:18:47","slug":"pandalar-csvyi-farkli-sayida-sutunla-okur","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/pandalar-csvyi-farkli-sayida-sutunla-okur\/","title":{"rendered":"Pandalar: csv'yi sat\u0131r ba\u015f\u0131na farkl\u0131 say\u0131da s\u00fctunla i\u00e7e aktar\u0131n"},"content":{"rendered":"

<\/p>\n

\n

Sat\u0131r ba\u015f\u0131na farkl\u0131 say\u0131da s\u00fctun oldu\u011funda bir CSV dosyas\u0131n\u0131 pandalara aktarmak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n

 df = pd. read_csv<\/span> (' uneven_data.csv<\/span> ', header= None<\/span> , names=range( 4<\/span> ))<\/span>\n<\/span><\/strong><\/pre>\n
 range()<\/strong> fonksiyonunun i\u00e7indeki de\u011fer, sat\u0131rdaki maksimum s\u00fctun say\u0131s\u0131na sahip s\u00fctun say\u0131s\u0131 olmal\u0131d\u0131r.<\/span><\/p>\n
 A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n
 \u00d6rnek: CSV’yi sat\u0131r ba\u015f\u0131na farkl\u0131 say\u0131da s\u00fctunla Pandas’a aktar\u0131n<\/strong><\/span><\/h2>\n
 Diyelim ki d\u00fczensiz_data.csv<\/strong> ad\u0131nda a\u015fa\u011f\u0131daki CSV dosyam\u0131z var:<\/span> <\/p>\n
\"\"<\/p>\n
 Her sat\u0131r\u0131n ayn\u0131 say\u0131da s\u00fctuna sahip olmad\u0131\u011f\u0131n\u0131 unutmay\u0131n.<\/span><\/p>\n
 Bu CSV dosyas\u0131n\u0131 bir pandas DataFrame’e aktarmak i\u00e7in read_csv()<\/strong> i\u015flevini kullanmaya \u00e7al\u0131\u015f\u0131rsak bir hata al\u0131r\u0131z:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#attempt to import CSV file with differing number of columns per row\ndf = pd. read_csv<\/span> (' uneven_data.csv<\/span> ', header= None<\/span> )\n\nParserError: Error tokenizing data. C error: Expected 2 fields in line 2, saw 4\n<\/span><\/span><\/strong><\/span><\/b><\/pre>\n
 Bize pandalar\u0131n 2<\/strong> alan bekledi\u011fini s\u00f6yleyen bir ParserError<\/strong> al\u0131yoruz (\u00e7\u00fcnk\u00fc bu ilk sat\u0131rdaki s\u00fctun say\u0131s\u0131yd\u0131), ancak 4<\/strong> g\u00f6rd\u00fc.<\/span><\/span><\/p>\n
 Bu hata bize belirli bir sat\u0131rdaki maksimum s\u00fctun say\u0131s\u0131n\u0131n 4<\/strong> oldu\u011funu s\u00f6yler.<\/span><\/p>\n
 B\u00f6ylece CSV dosyas\u0131n\u0131 i\u00e7e aktarabilir ve name<\/strong> arg\u00fcman\u0131na range(4)<\/strong> de\u011ferini sa\u011flayabiliriz:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#import CSV file with differing number of columns per row\ndf = pd. read_csv<\/span> (' uneven_data.csv<\/span> ', header= None<\/span> , names=range( 4<\/span> )))\n\n#view DataFrame<\/span>\nprint<\/span> (df)\n\n   0 1 2 3\n0 to 22 NaN NaN\n1 B 16 10.0 12.0\n2 C 25 10.0 NaN\n3 D 14 2.0 7.0\n4 E 20 4.0 NaN\n<\/span><\/span><\/strong><\/span><\/b><\/pre>\n
 Pandalara 4 s\u00fctun beklemelerini a\u00e7\u0131k\u00e7a s\u00f6yledi\u011fimiz i\u00e7in CSV dosyas\u0131n\u0131 herhangi bir hata olmadan pandas DataFrame’e ba\u015far\u0131l\u0131 bir \u015fekilde aktarabildi\u011fimizi unutmay\u0131n.<\/span><\/p>\n
 Pandalar varsay\u0131lan olarak her sat\u0131rdaki t\u00fcm eksik de\u011ferleri NaN ile doldurur.<\/span><\/p>\n
 Eksik de\u011ferlerin s\u0131f\u0131r olarak g\u00f6r\u00fcnmesini istiyorsan\u0131z fillna()<\/strong> fonksiyonunu a\u015fa\u011f\u0131daki gibi kullanabilirsiniz:<\/span><\/p>\n
 #fill NaN values with zeros\n<\/span>df_new = df. fillna<\/span> ( 0<\/span> )\n\n#view new DataFrame\n<\/span>print<\/span> (df_new)\n\n   0 1 2 3\n0 to 22 0.0 0.0\n1 B 16 10.0 12.0\n2 C 25 10.0 0.0\n3 D 14 2.0 7.0\n4 E 20 4.0 0.0<\/b><\/pre>\n
 DataFrame’deki her NaN de\u011feri art\u0131k s\u0131f\u0131rla de\u011fi\u015ftirildi.<\/span><\/p>\n
 Not<\/strong> : Pandalar\u0131n read_csv()<\/strong> i\u015flevinin tam belgelerini burada<\/a> bulabilirsiniz.<\/span><\/p>\n
 Ek kaynaklar<\/strong><\/span><\/h2>\n
 A\u015fa\u011f\u0131daki e\u011fitimlerde Python’da di\u011fer genel g\u00f6revlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n
 Pandalar: CSV dosyas\u0131n\u0131 okurken sat\u0131rlar nas\u0131l atlan\u0131r<\/a>
 Pandalar: Mevcut bir CSV dosyas\u0131na nas\u0131l veri eklenir?<\/a>
 Pandalar: CSV dosyas\u0131n\u0131 i\u00e7e aktar\u0131rken t\u00fcrler nas\u0131l belirtilir?<\/a>
Pandalar: CSV dosyas\u0131n\u0131 i\u00e7e aktar\u0131rken s\u00fctun adlar\u0131n\u0131 ayarlay\u0131n<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
Sat\u0131r ba\u015f\u0131na farkl\u0131 say\u0131da s\u00fctun oldu\u011funda bir CSV dosyas\u0131n\u0131 pandalara aktarmak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz: df = pd. read_csv (‘ uneven_data.csv ‘, header= None , names=range( 4 )) range() fonksiyonunun i\u00e7indeki de\u011fer, sat\u0131rdaki maksimum s\u00fctun say\u0131s\u0131na sahip s\u00fctun say\u0131s\u0131 olmal\u0131d\u0131r. A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir. \u00d6rnek: CSV’yi sat\u0131r ba\u015f\u0131na farkl\u0131 say\u0131da […]<\/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-4084","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\nPandalar: sat\u0131r ba\u015f\u0131na farkl\u0131 say\u0131da s\u00fctun i\u00e7eren bir CSV dosyas\u0131n\u0131 i\u00e7e aktar\u0131n \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"Bu e\u011fitimde, bir \u00f6rnek de dahil olmak \u00fczere sat\u0131r ba\u015f\u0131na farkl\u0131 say\u0131da s\u00fctun oldu\u011funda CSV'nin pandalara nas\u0131l aktar\u0131laca\u011f\u0131 a\u00e7\u0131klanmaktad\u0131r.\" \/>\n<meta name=\"robots\" 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