<\/p>\n
Bir NumPy dizisindeki belirli bir de\u011ferden b\u00fcy\u00fck \u00f6\u011felerin say\u0131s\u0131n\u0131 saymak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n Bu \u00f6zel \u00f6rnek, data<\/strong> ad\u0131 verilen NumPy dizisindeki 10’dan b\u00fcy\u00fck \u00f6\u011felerin say\u0131s\u0131n\u0131 d\u00f6nd\u00fcrecektir.<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n Toplamda 15 \u00f6\u011feli a\u015fa\u011f\u0131daki 2D NumPy dizisine sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n Dizideki de\u011feri 10’dan b\u00fcy\u00fck olan \u00f6\u011felerin toplam say\u0131s\u0131n\u0131 saymak i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabiliriz:<\/span><\/p>\n Sonu\u00e7tan NumPy dizisindeki 4<\/strong> de\u011ferin 10’dan b\u00fcy\u00fck oldu\u011funu g\u00f6rebiliriz.<\/span><\/p>\n NumPy dizisini manuel olarak incelersek d\u00f6rt \u00f6\u011fenin (11, 12, 13, 14) ger\u00e7ekten 10’dan b\u00fcy\u00fck oldu\u011funu do\u011frulayabiliriz.<\/span><\/p>\n 10’dan k\u00fc\u00e7\u00fck eleman say\u0131s\u0131n\u0131 bulmak i\u00e7in k\u00fc\u00e7\u00fckt\u00fcr operat\u00f6r\u00fcn\u00fc ( <<\/strong> ) kullanabiliriz:<\/span><\/p>\n Sonu\u00e7tan NumPy dizisindeki 10<\/b> de\u011ferin 10’dan k\u00fc\u00e7\u00fck oldu\u011funu g\u00f6rebiliriz.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde Python’da di\u011fer yayg\u0131n i\u015flemlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n NumPy’de NaN’ye e\u015fit elemanlar\u0131n say\u0131s\u0131 nas\u0131l say\u0131l\u0131r?<\/a> Bir NumPy dizisindeki belirli bir de\u011ferden b\u00fcy\u00fck \u00f6\u011felerin say\u0131s\u0131n\u0131 saymak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz: import numpy as np vals_greater_10 = (data > 10 ). sum () Bu \u00f6zel \u00f6rnek, data ad\u0131 verilen NumPy dizisindeki 10’dan b\u00fcy\u00fck \u00f6\u011felerin say\u0131s\u0131n\u0131 d\u00f6nd\u00fcrecektir. A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir. \u00d6rnek: NumPy dizisindeki de\u011ferden b\u00fcy\u00fck olan \u00f6\u011felerin […]<\/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-4304","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n import<\/span> numpy as<\/span> np\n\nvals_greater_10 = (data ><\/span> 10<\/span> ). sum<\/span> ()\n<\/strong><\/pre>\n \u00d6rnek: NumPy dizisindeki de\u011ferden b\u00fcy\u00fck olan \u00f6\u011felerin say\u0131s\u0131n\u0131 say\u0131n<\/strong><\/span><\/h2>\n
import<\/span> numpy as<\/span> np\n\n#create 2D NumPy array with 3 columns and 5 rows\n<\/span>data = np. matrix<\/span> (np. arange<\/span> (15). reshape<\/span> ((5, 3)))\n\n#view NumPy array\n<\/span>print<\/span> (data)\n\n[[ 0 1 2]\n [3 4 5]\n [6 7 8]\n [9 10 11]\n [12 13 14]]\n<\/span><\/span><\/strong><\/pre>\n #count number of values greater than 10 in NumPy matrix\n<\/span>vals_greater_10 = (data ><\/span> 10<\/span> ). sum<\/span> ()\n\n#view results\n<\/span>print<\/span> (vals_greater_10)\n\n4<\/span><\/span><\/strong><\/pre>\n #count number of values less than 10 in NumPy matrix\n<\/span>vals_less_10 = (data <<\/span> 10<\/span> ). sum<\/span> ()\n\n#view results\n<\/span>print<\/span> (vals_less_10)\n\n10<\/span><\/span><\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
NumPy’de s\u0131f\u0131ra e\u015fit \u00f6\u011felerin say\u0131s\u0131 nas\u0131l say\u0131l\u0131r?<\/a>
NumPy’de True’ya e\u015fit \u00f6\u011felerin say\u0131s\u0131 nas\u0131l say\u0131l\u0131r?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"