<\/p>\n
Pandas DataFrame’in bir s\u00fctunundaki de\u011ferlerin k\u00fcm\u00fclatif y\u00fczdesini hesaplamak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n Bir \u015firketin ard\u0131\u015f\u0131k y\u0131llarda satt\u0131\u011f\u0131 birimlerin say\u0131s\u0131n\u0131 g\u00f6steren a\u015fa\u011f\u0131daki panda DataFrame’e sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n Daha sonra, sat\u0131lan birimlerin k\u00fcm\u00fclatif say\u0131s\u0131n\u0131 ve sat\u0131lan birimlerin k\u00fcm\u00fclatif y\u00fczdesini g\u00f6r\u00fcnt\u00fcleyen bir s\u00fctun eklemek i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/span><\/p>\n K\u00fcm\u00fclatif y\u00fczdeleri \u015fu \u015fekilde yorumluyoruz:<\/span><\/p>\n Ve benzeri.<\/span><\/p>\n G\u00f6r\u00fcnt\u00fclenen ondal\u0131k basamak say\u0131s\u0131n\u0131 da de\u011fi\u015ftirmek i\u00e7in round()<\/strong> i\u015flevindeki de\u011feri kolayca de\u011fi\u015ftirebilece\u011finizi unutmay\u0131n.<\/span><\/p>\n \u00d6rne\u011fin, bunun yerine k\u00fcm\u00fclatif y\u00fczdeyi s\u0131f\u0131r ondal\u0131k basama\u011fa yuvarlayabiliriz:<\/span><\/p>\n K\u00fcm\u00fclatif y\u00fczdeler art\u0131k s\u0131f\u0131r ondal\u0131k basama\u011fa yuvarlan\u0131yor.<\/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 Python’da Frekans Tablolar\u0131 Nas\u0131l Olu\u015fturulur<\/a> Pandas DataFrame’in bir s\u00fctunundaki de\u011ferlerin k\u00fcm\u00fclatif y\u00fczdesini hesaplamak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz: #calculate cumulative sum of column df[‘ cum_sum ‘] = df[‘ col1 ‘]. cumsum () #calculate cumulative percentage of column (rounded to 2 decimal places) df[‘ cum_percent ‘] = round( 100 *df. cum_sum \/df[‘ col1 ‘]. sum (), 2 ) A\u015fa\u011f\u0131daki \u00f6rnek, bu […]<\/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-2572","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n #calculate cumulative sum of column\n<\/span>df[' cum_sum<\/span> '] = df[' col1<\/span> ']. cumsum<\/span> ()\n\n#calculate cumulative percentage of column (rounded to 2 decimal places)\n<\/span>df[' cum_percent<\/span> '] = round( 100<\/span> *df. cum_sum<\/span> \/df[' col1<\/span> ']. sum<\/span> (), 2<\/span> )\n<\/strong><\/pre>\n \u00d6rnek: Pandalar aras\u0131ndaki k\u00fcm\u00fclatif y\u00fczdeyi hesaplay\u0131n<\/strong><\/span><\/h3>\n
import<\/span> pandas as<\/span> pd\n\n#createDataFrame\ndf = pd. DataFrame<\/span> ({' year<\/span> ': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],\n ' units_sold<\/span> ': [60, 75, 77, 87, 104, 134, 120, 125, 140, 150]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n year units_sold\n0 1 60\n1 2 75\n2 3 77\n3 4 87\n4 5 104\n5 6 134\n6 7 120\n7 8 125\n8 9 140\n9 10 150\n<\/span><\/span><\/strong><\/pre>\n #calculate cumulative sum of units sold\n<\/span>df[' cum_sum<\/span> '] = df[' units_sold<\/span> ']. cumsum<\/span> ()\n\n#calculate cumulative percentage of units sold\n<\/span>df[' cum_percent<\/span> '] = round( 100<\/span> *df. cum_sum<\/span> \/df[' units_sold<\/span> ']. sum<\/span> (), 2<\/span> )\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n year units_sold cum_sum cum_percent\n0 1 60 60 5.60\n1 2 75 135 12.59\n2 3 77 212 19.78\n3 4 87 299 27.89\n4 5 104 403 37.59\n5 6 134 537 50.09\n6 7 120 657 61.29\n7 8 125 782 72.95\n8 9 140 922 86.01\n9 10 150 1072 100.00\n<\/span><\/span><\/strong><\/pre>\n\n
#calculate cumulative sum of units sold\n<\/span>df[' cum_sum<\/span> '] = df[' units_sold<\/span> ']. cumsum<\/span> ()\n\n#calculate cumulative percentage of units sold\n<\/span>df[' cum_percent<\/span> '] = round( 100<\/span> *df. cum_sum<\/span> \/df[' units_sold<\/span> ']. sum<\/span> (), 0<\/span> )\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n year units_sold cum_sum cum_percent\n0 1 60 60 6.0\n1 2 75 135 13.0\n2 3 77 212 20.0\n3 4 87 299 28.0\n4 5 104 403 38.0\n5 6 134 537 50.0\n6 7 120 657 61.0\n7 8 125 782 73.0\n8 9 140 922 86.0\n9 10 150 1072 100.0<\/span><\/span><\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h3>\n
Python’da G\u00f6reli Frekans Nas\u0131l Hesaplan\u0131r?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"