{"id":4079,"date":"2023-07-13T18:11:11","date_gmt":"2023-07-13T18:11:11","guid":{"rendered":"https:\/\/statorials.org\/tr\/pandalar-csvyi-okur-ilk-sutunu-gormezden-gelir\/"},"modified":"2023-07-13T18:11:11","modified_gmt":"2023-07-13T18:11:11","slug":"pandalar-csvyi-okur-ilk-sutunu-gormezden-gelir","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/pandalar-csvyi-okur-ilk-sutunu-gormezden-gelir\/","title":{"rendered":"Pandalar: csv dosyas\u0131n\u0131 i\u00e7e aktar\u0131rken ilk s\u00fctunu yoksay"},"content":{"rendered":"

<\/p>\n

\n

Bir CSV dosyas\u0131n\u0131 pandas DataFrame’e aktar\u0131rken ilk s\u00fctunu yok saymak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n

 with<\/span> open<\/span> (' basketball_data.csv<\/span> ') as<\/span> x:\n    ncols = len<\/span> ( x.readline<\/span> (). split<\/span> (' ,<\/span> '))\n\ndf = pd. read_csv<\/span> (' basketball_data.csv<\/span> ', usecols= range<\/span> (1,ncols))\n<\/strong><\/pre>\n
 Bu \u00f6zel \u00f6rnek, basketbol_data.csv<\/strong> adl\u0131 bir CSV dosyas\u0131n\u0131n ilk s\u00fctun hari\u00e7 her s\u00fctununu bir pandas DataFrame’e okuyacakt\u0131r.<\/span><\/p>\n
 Bu kodu kullanarak \u00f6ncelikle CSV dosyas\u0131ndaki s\u00fctun say\u0131s\u0131n\u0131 bulup bunu ncols<\/strong> adl\u0131 bir de\u011fi\u015fkene atad\u0131k.<\/span><\/p>\n
 Daha sonra, CSV dosyas\u0131n\u0131n yaln\u0131zca 1 (yani ikinci s\u00fctun) ile son s\u00fctunu aras\u0131ndaki s\u00fctunlar\u0131 i\u00e7e aktarmak istedi\u011fimizi belirtmek i\u00e7in usecols<\/strong> arg\u00fcman\u0131n\u0131 kullan\u0131yoruz.<\/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: Bir CSV dosyas\u0131n\u0131 Pandas’a aktar\u0131rken ilk s\u00fctunu dikkate almay\u0131n<\/strong><\/span><\/h2>\n
 Diyelim ki basketbol_data.csv<\/strong> ad\u0131nda a\u015fa\u011f\u0131daki CSV dosyam\u0131z var:<\/span> <\/p>\n
\"\"<\/p>\n
 CSV dosyas\u0131n\u0131 bir pandas DataFrame’e aktarmak ve ilk s\u00fctunu yok saymak i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabiliriz:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#calculate number of columns in CSV file\n<\/span>with open<\/span> (' basketball_data.csv<\/span> ') as<\/span> x:\n    ncols = len<\/span> ( x.readline<\/span> (). split<\/span> (' ,<\/span> '))\n\n#import all columns except first column into DataFrame\n<\/span>df = pd. read_csv<\/span> (' basketball_data.csv<\/span> ', usecols= range<\/span> (1,ncols))\n\n#view resulting DataFrame\n<\/span>print<\/span> (df)\n\n   rebound points\n0 22 10\n1 14 9\n2 29 6\n3 30 2\n<\/strong><\/span><\/b><\/pre>\n
 CSV dosyas\u0131n\u0131 pandalara aktard\u0131\u011f\u0131m\u0131zda ekip<\/strong> ad\u0131 verilen ilk s\u00fctunun kald\u0131r\u0131ld\u0131\u011f\u0131n\u0131 unutmay\u0131n.<\/span><\/p>\n
 CSV dosyas\u0131ndaki toplam s\u00fctun say\u0131s\u0131n\u0131 \u00f6nceden biliyorsan\u0131z, bu de\u011feri do\u011frudan usecols<\/strong> arg\u00fcman\u0131na sa\u011flayabilece\u011finizi unutmay\u0131n.<\/span><\/p>\n
 \u00d6rne\u011fin, CVS dosyas\u0131nda \u00fc\u00e7 s\u00fctun bulundu\u011funu zaten bildi\u011fimizi varsayal\u0131m.<\/span><\/p>\n
 CSV dosyas\u0131n\u0131 bir pandas DataFrame’e aktarmak ve ilk s\u00fctunu yok saymak i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabiliriz:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#import all columns except first column into DataFrame\n<\/span>df = pd. read_csv<\/span> (' basketball_data.csv<\/span> ', usecols= range<\/span> (1,3))\n\n#view resulting DataFrame\n<\/span>print<\/span> (df)\n\n   rebound points\n0 22 10\n1 14 9\n2 29 6\n3 30 2<\/strong><\/span><\/b><\/pre>\n
 CSV dosyas\u0131n\u0131 pandalara aktard\u0131\u011f\u0131m\u0131zda ekip<\/strong> ad\u0131 verilen ilk s\u00fctunun kald\u0131r\u0131ld\u0131\u011f\u0131n\u0131 unutmay\u0131n.<\/span><\/p>\n
 CSV dosyas\u0131nda \u00fc\u00e7 s\u00fctun oldu\u011funu zaten bildi\u011fimizden, usecols<\/strong> arg\u00fcman\u0131nda basit\u00e7e range(1,3)<\/strong> kulland\u0131k.<\/span><\/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: read_csv’nin usecols arg\u00fcman\u0131yla nas\u0131l kullan\u0131laca\u011f\u0131<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
Bir CSV dosyas\u0131n\u0131 pandas DataFrame’e aktar\u0131rken ilk s\u00fctunu yok saymak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz: with open (‘ basketball_data.csv ‘) as x: ncols = len ( x.readline (). split (‘ , ‘)) df = pd. read_csv (‘ basketball_data.csv ‘, usecols= range (1,ncols)) Bu \u00f6zel \u00f6rnek, basketbol_data.csv adl\u0131 bir CSV dosyas\u0131n\u0131n ilk s\u00fctun hari\u00e7 her s\u00fctununu […]<\/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-4079","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\nPandalar: CSV dosyas\u0131n\u0131 i\u00e7e aktar\u0131rken ilk s\u00fctunu dikkate almay\u0131n - Statorials<\/title>\n<meta name=\"description\" content=\"Bu e\u011fitimde bir CSV dosyas\u0131n\u0131 pandas DataFrame'e aktar\u0131rken ilk s\u00fctunun nas\u0131l yok say\u0131laca\u011f\u0131 bir \u00f6rnekle a\u00e7\u0131klanmaktad\u0131r.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/tr\/pandalar-csvyi-okur-ilk-sutunu-gormezden-gelir\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandalar: CSV dosyas\u0131n\u0131 i\u00e7e aktar\u0131rken ilk s\u00fctunu dikkate almay\u0131n - 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