Y\u00f6ntem 1: Belirli bir sat\u0131r\u0131 atla<\/strong><\/span><\/p>\n Y\u00f6ntem 2: Birden \u00c7ok Belirli Sat\u0131r\u0131n Yoksay\u0131lmas\u0131<\/strong><\/span><\/p>\n Y\u00f6ntem 3: ilk N sat\u0131r\u0131 yoksay<\/strong><\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnekler, her y\u00f6ntemin, player_data.xlsx<\/strong> adl\u0131 a\u015fa\u011f\u0131daki Excel dosyas\u0131yla pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span> <\/p>\n Excel dosyas\u0131n\u0131 i\u00e7e aktarmak ve dizin konumu 2’deki sat\u0131r\u0131 yok saymak i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n Excel dosyas\u0131 pandalar\u0131n DataFrame’ine aktar\u0131l\u0131rken dizin konumu 2’deki sat\u0131r\u0131n (‘B’ ekibiyle birlikte) g\u00f6z ard\u0131 edildi\u011fini unutmay\u0131n.<\/span><\/p>\n Not<\/strong> : Excel dosyas\u0131n\u0131n ilk sat\u0131r\u0131 0. sat\u0131r olarak kabul edilir.<\/span><\/p>\n Excel dosyas\u0131n\u0131 i\u00e7e aktarmak ve dizin konumu 2 ve 4’teki sat\u0131rlar\u0131 yok saymak i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n Excel dosyas\u0131 pandas DataFrame’e aktar\u0131l\u0131rken dizin konumu 2 ve 4’teki (“B” ve “D” ekipleriyle) sat\u0131rlar\u0131n g\u00f6z ard\u0131 edildi\u011fini unutmay\u0131n.<\/span><\/p>\n Excel dosyas\u0131n\u0131 i\u00e7e aktarmak ve ilk iki sat\u0131r\u0131 yok saymak i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n Excel dosyas\u0131n\u0131n ilk iki sat\u0131r\u0131n\u0131n atland\u0131\u011f\u0131n\u0131 ve sonraki kullan\u0131labilir sat\u0131r\u0131n (“B” ekibiyle birlikte) DataFrame’in ba\u015fl\u0131k sat\u0131r\u0131 haline geldi\u011fini unutmay\u0131n.<\/span><\/p>\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 ile Excel dosyalar\u0131 nas\u0131l okunur<\/a> Bir Excel dosyas\u0131n\u0131 pandas DataFrame’e okurken sat\u0131rlar\u0131 atlamak i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemleri kullanabilirsiniz: Y\u00f6ntem 1: Belirli bir sat\u0131r\u0131 atla #import DataFrame and skip row in index position 2 df = pd. read_excel (‘ my_data.xlsx ‘, skiprows=[ 2 ]) Y\u00f6ntem 2: Birden \u00c7ok Belirli Sat\u0131r\u0131n Yoksay\u0131lmas\u0131 #import DataFrame and skip rows in index positions 2 and 4 […]<\/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-4086","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n #import DataFrame and skip row in index position 2\n<\/span>df = pd. read_excel<\/span> (' my_data.xlsx<\/span> ', skiprows=[ 2<\/span> ])\n<\/strong><\/pre>\n #import DataFrame and skip rows in index positions 2 and 4\n<\/span>df = pd. read_excel<\/span> (' my_data.xlsx<\/span> ' , skiprows=[2,4<\/span> ]<\/span> )<\/strong><\/pre>\n #import DataFrame and skip first 2 rows\n<\/span>df = pd. read_excel<\/span> (' my_data.xlsx<\/span> ', skiprows= 2<\/span> )<\/strong><\/pre>\n![\"\"](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/sauter-excel1.png\")
<\/p>\n \u00d6rnek 1: Belirli bir sat\u0131r\u0131 yoksayma<\/strong><\/span><\/h2>\n
import<\/span> pandas as<\/span> pd\n\n#import DataFrame and skip row in index position 2\n<\/span>df = pd. read_excel<\/span> (' player_data.xlsx<\/span> ', skiprows=[ 2<\/span> ])\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n team points rebound assists\n0 to 24 8 5\n1 C 15 4 7\n2 D 19 4 8\n3 E 32 6 8\n4 F 13 7 9\n<\/b><\/pre>\n \u00d6rnek 2: Birden fazla belirli sat\u0131r\u0131n g\u00f6z ard\u0131 edilmesi<\/strong><\/span><\/h2>\n
import<\/span> pandas as<\/span> pd\n\n#import DataFrame and skip rows in index positions 2 and 4\n<\/span>df = pd. read_excel<\/span> (' player_data.xlsx<\/span> ', skiprows=[ 2,4<\/span> ] )<\/span>\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n team points rebound assists\n0 to 24 8 5\n1 C 15 4 7\n2 E 32 6 8\n3 F 13 7 9\n<\/b><\/pre>\n \u00d6rnek 3: ilk N sat\u0131r\u0131 dikkate almay\u0131n<\/strong><\/span><\/h2>\n
import<\/span> pandas as<\/span> pd\n\n#import DataFrame and skip first 2 rows\n<\/span>df = pd. read_excel<\/span> (' player_data.xlsx<\/span> ', skiprows= 2<\/span> )\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n B 20 12 3\n0 C 15 4 7\n1 D 19 4 8\n2 E 32 6 8\n3 F 13 7 9\n<\/b><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
Pandas DataFrame’i Excel’e nas\u0131l aktar\u0131r\u0131m<\/a>
NumPy dizisi CSV dosyas\u0131na nas\u0131l aktar\u0131l\u0131r<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"