{"id":3199,"date":"2023-07-18T17:44:30","date_gmt":"2023-07-18T17:44:30","guid":{"rendered":"https:\/\/statorials.org\/tr\/pandalar-grup-donusumu\/"},"modified":"2023-07-18T17:44:30","modified_gmt":"2023-07-18T17:44:30","slug":"pandalar-grup-donusumu","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/pandalar-grup-donusumu\/","title":{"rendered":"Pandalarda groupby() ve transform() i\u015flevleri nas\u0131l kullan\u0131l\u0131r?"},"content":{"rendered":"

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Bir pandan\u0131n DataFrame’inde groupby()<\/strong> ve transform()<\/strong> i\u015flevlerini birlikte kullanmak i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemleri kullanabilirsiniz:<\/span><\/p>\n

Y\u00f6ntem 1: Yerle\u015fik i\u015flevle groupby() ve transform()’u kullan\u0131n<\/strong><\/span><\/p>\n

 df[' new<\/span> '] = df. groupby<\/span> (' group_var<\/span> ')[' value_var<\/span> ']. transform<\/span> (' mean<\/span> ')\n<\/strong><\/pre>\n
 Y\u00f6ntem 2: groupby() ve transform()’u \u00f6zel bir i\u015flevle kullanma<\/strong><\/span><\/p>\n
 df[' new<\/span> '] = df. groupby<\/span> (' group_var<\/span> ')[' value_var<\/span> ']. transform<\/span> ( lambda<\/span> x: some function)<\/strong><\/pre>\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
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],\n                   ' points<\/span> ': [30, 22, 19, 14, 14, 11, 20, 28]})\n\n#view DataFrame\nprint<\/span><\/span> (df)\n\n  team points\n0 to 30\n1 to 22\n2 to 19\n3 to 14\n4 B 14\n5 B 11\n6 B 20\n7 B 28\n<\/b><\/pre>\n
 \u00d6rnek 1: Groupby() ve transform()’u yerle\u015fik i\u015flevle kullanma<\/strong><\/span><\/h3>\n
 A\u015fa\u011f\u0131daki kod, DataFrame’e ortalama_noktalar ad\u0131 verilen yeni bir s\u00fctun eklemek i\u00e7in groupby(<\/strong> ) ve transform()<\/strong> i\u015flevlerinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n
 #create new column called mean_points\ndf[' mean_points<\/span> '] = df. groupby<\/span> (' team<\/span> ')[' points<\/span> ']. transform<\/span> (' mean<\/span> ')\n<\/span>\n#view updated DataFrame\nprint<\/span> (df)\n\n  team points mean_points\n0 to 30 21.25\n1 to 22 21.25\n2 A 19 21.25\n3 to 14 21.25\n4 B 14 18.25\n5 B 11 18.25\n6 B 20 18.25\n7 B 28 18.25<\/span><\/span><\/strong><\/pre>\n
 A Tak\u0131m\u0131ndaki oyuncular\u0131n ortalama puan de\u011feri 21,25<\/strong> ve B Tak\u0131m\u0131ndaki oyuncular\u0131n ortalama puan de\u011feri 18,25<\/strong> oldu, dolay\u0131s\u0131yla bu de\u011ferler yeni bir s\u00fctunda her oyuncuya g\u00f6re atand\u0131.<\/span><\/p>\n
 Her tak\u0131m\u0131n ald\u0131\u011f\u0131 puanlar\u0131n toplam\u0131n\u0131 g\u00f6steren yeni bir s\u00fctun olu\u015fturmak i\u00e7in sum()<\/strong> gibi ba\u015fka bir yerle\u015fik i\u015flevi de kullanabilece\u011fimizi unutmay\u0131n:<\/span><\/p>\n
 #create new column called sum_points\ndf[' sum_points<\/span> '] = df. groupby<\/span> (' team<\/span> ')[' points<\/span> ']. transform<\/span> (' sum<\/span> ')\n<\/span>\n#view updated DataFrame\nprint<\/span> (df)\n\n  team points sum_points\n0 to 30 85\n1 to 22 85\n2 A 19 85\n3 to 14 85\n4 B 14 73\n5 B 11 73\n6 B 20 73\n7 B 28 73<\/span><\/span><\/strong><\/pre>\n
 A tak\u0131m\u0131 oyuncular\u0131n\u0131n puanlar\u0131n\u0131n toplam\u0131 85<\/b> , B tak\u0131m\u0131 oyuncular\u0131n\u0131n puanlar\u0131n\u0131n toplam\u0131 73<\/strong> oldu, dolay\u0131s\u0131yla bu de\u011ferler yeni bir s\u00fctunda her oyuncuya uygun \u015fekilde atand\u0131.<\/span><\/p>\n
 \u00d6rnek 2: Groupby() ve transform()’u \u00f6zel bir i\u015flevle kullanma<\/strong><\/span><\/h3>\n
 A\u015fa\u011f\u0131daki kod, her oyuncunun kendi tak\u0131mlar\u0131nda att\u0131\u011f\u0131 toplam puanlar\u0131n y\u00fczdesini hesaplayan \u00f6zel bir i\u015flev olu\u015fturmak i\u00e7in groupby(<\/strong> ) ve transform()<\/strong> i\u015flevlerinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n
 #create new column called percent_of_points\ndf[' percent_of_points<\/span> '] = df. groupby<\/span> (' team<\/span> ')[' points<\/span> ']. transform<\/span> ( lambda<\/span> x:x\/ x.sum<\/span> ())\n<\/span>\n#view updated DataFrame\nprint<\/span> (df)\n\n  team points percent_of_points\n0 A 30 0.352941\n1 A 22 0.258824\n2 A 19 0.223529\n3 A 14 0.164706\n4 B 14 0.191781\n5 B 11 0.150685\n6 B 20 0.273973\n7 B 28 0.383562\n<\/span><\/span><\/strong><\/pre>\n
 Sonucun nas\u0131l yorumlanaca\u011f\u0131 a\u015fa\u011f\u0131da a\u00e7\u0131klanm\u0131\u015ft\u0131r:<\/span><\/span><\/p>\n