<\/p>\n
Pandas DataFrame’deki kopyalar\u0131 saymak i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemleri kullanabilirsiniz:<\/span><\/p>\n Y\u00f6ntem 1: Bir s\u00fctundaki yinelenen de\u011ferleri say\u0131n<\/strong><\/span><\/p>\n Y\u00f6ntem 2: Yinelenen sat\u0131rlar\u0131 sayma<\/strong><\/span><\/p>\n Y\u00f6ntem 3: Her benzersiz sat\u0131r i\u00e7in kopyalar\u0131 say\u0131n<\/strong><\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnekler, her y\u00f6ntemin pratikte a\u015fa\u011f\u0131daki pandalar DataFrame ile nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, puan<\/strong> s\u00fctunundaki yinelenen de\u011ferlerin say\u0131s\u0131n\u0131n nas\u0131l say\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n Puan<\/strong> s\u00fctununda 4 adet<\/strong> yinelenen de\u011ferin oldu\u011funu g\u00f6rebiliriz.<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, DataFrame’deki yinelenen sat\u0131rlar\u0131n say\u0131s\u0131n\u0131n nas\u0131l say\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n DataFrame’de 2<\/strong> kopya sat\u0131r oldu\u011funu g\u00f6rebiliriz.<\/span><\/p>\n Bu 2 yinelenen sat\u0131r\u0131 g\u00f6r\u00fcnt\u00fclemek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabiliriz:<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, DataFrame’deki her benzersiz sat\u0131r i\u00e7in kopya say\u0131s\u0131n\u0131n nas\u0131l say\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n Boyut<\/strong> s\u00fctunu, her benzersiz sat\u0131r i\u00e7in kopya say\u0131s\u0131n\u0131 g\u00f6r\u00fcnt\u00fcler.<\/span><\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde pandalarda di\u011fer yayg\u0131n i\u015flemlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n Pandalar’da yinelenen sat\u0131rlar nas\u0131l kald\u0131r\u0131l\u0131r<\/a> Pandas DataFrame’deki kopyalar\u0131 saymak i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemleri kullanabilirsiniz: Y\u00f6ntem 1: Bir s\u00fctundaki yinelenen de\u011ferleri say\u0131n len (df[‘ my_column ‘]) – len (df[‘ my_column ‘]. drop_duplicates ()) Y\u00f6ntem 2: Yinelenen sat\u0131rlar\u0131 sayma len (df) -len ( df.drop_duplicates ()) Y\u00f6ntem 3: Her benzersiz sat\u0131r i\u00e7in kopyalar\u0131 say\u0131n df. groupby ( df.columns.tolist (), as_index= False ) . size […]<\/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-3315","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n len<\/span> (df[' my_column<\/span> ']) - len<\/span> (df[' my_column<\/span> ']. drop_duplicates<\/span> ())\n<\/strong><\/pre>\n len<\/span> (df) -len<\/span> ( df.drop_duplicates<\/span> ())<\/strong><\/span><\/pre>\n df. groupby<\/span> ( df.columns.tolist<\/span> (), as_index= False<\/span> ) .<\/span> size<\/span> ()<\/strong><\/span><\/pre>\n import<\/span> pandas as<\/span> pd\n\n#createDataFrame\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],\n ' position<\/span> ': ['G', 'G', 'G', 'F', 'G', 'G', 'F', 'F'],\n ' points<\/span> ': [5, 5, 8, 10, 5, 7, 10, 10]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n team position points\n0 AG 5\n1 GA 5\n2 AG 8\n3 AF 10\n4 BG 5\n5 BG 7\n6 BF 10\n7 BF 10<\/span><\/span><\/strong><\/pre>\n \u00d6rnek 1: Bir s\u00fctundaki yinelenen de\u011ferleri sayma<\/strong><\/span><\/h2>\n
#count duplicate values in points column\n<\/span>len<\/span> (df[' points<\/span> '])- len<\/span> (df[' points<\/span> ']. drop_duplicates<\/span> ())\n\n4<\/span><\/span><\/strong><\/pre>\n \u00d6rnek 2: Yinelenen sat\u0131rlar\u0131 sayma<\/strong><\/span><\/h2>\n
#count number of duplicate rows<\/span>\nlen<\/span> (df) -len<\/span> ( df.drop_duplicates<\/span> ())\n\n2<\/strong><\/span><\/pre>\n #display duplicated rows<\/span>\ndf[df. duplicated<\/span> ()]\n\n team position points\n1 A G 5\n7 B F 10<\/span>\n<\/span><\/strong><\/span><\/pre>\n \u00d6rnek 3: Her benzersiz sat\u0131r i\u00e7in kopyalar\u0131 say\u0131n<\/strong><\/span><\/h2>\n
#display number of duplicates for each unique row\ndf. groupby<\/span> ( df.columns.tolist<\/span> (), as_index= False<\/span> ) .<\/span> size<\/span> ()\n\n team position points size\n0 A F 10 1\n1 A G 5 2\n2 A G 8 1\n3 B F 10 2\n4 B G 5 1\n5 B G 7 1\n<\/span><\/span><\/span><\/strong><\/span><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
Pandalar’da yinelenen s\u00fctunlar nas\u0131l kald\u0131r\u0131l\u0131r<\/a>
Pandalar’da dizine g\u00f6re s\u00fctunlar nas\u0131l se\u00e7ilir<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"