<\/p>\n
Bir pandan\u0131n DataFrame’inde groupby()<\/strong> i\u015flevini kulland\u0131ktan sonra belirli bir grubu elde etmek i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemleri kullanabilirsiniz:<\/span><\/p>\n Y\u00f6ntem 1: groupby()’yi kulland\u0131ktan sonra grubu al\u0131n<\/strong><\/span><\/p>\n Y\u00f6ntem 2: Groupby()’yi kulland\u0131ktan sonra gruptan belirli s\u00fctunlar\u0131 al\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, sat\u0131rlar\u0131 ma\u011faza ad\u0131na g\u00f6re gruplamak i\u00e7in groupby(<\/strong> ) i\u015flevinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 ve ard\u0131ndan “A” grup ad\u0131na sahip gruba ait t\u00fcm sat\u0131rlar\u0131 almak i\u00e7in get_group()<\/strong> i\u015flevinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n get_group()<\/strong> i\u015flevinin “A” grup ad\u0131na sahip gruba ait t\u00fcm sat\u0131rlar\u0131 d\u00f6nd\u00fcrd\u00fc\u011f\u00fcn\u00fc unutmay\u0131n.<\/span><\/span><\/p>\n A\u015fa\u011f\u0131daki kod, sat\u0131rlar\u0131 ma\u011faza ad\u0131na g\u00f6re gruplamak i\u00e7in groupby(<\/strong> ) i\u015flevinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131, ard\u0131ndan yaln\u0131zca “sat\u0131\u015f” ve “Geri \u00d6demeler” s\u00fctunlar\u0131 i\u00e7in grup ad\u0131 “A” olan gruba ait t\u00fcm sat\u0131rlar\u0131 almak \u00fczere get_group()<\/strong> i\u015flevinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir. :<\/span><\/p>\n get_group() i\u015flevinin<\/strong> yaln\u0131zca “sat\u0131\u015f” ve “geri \u00f6demeler” s\u00fctunlar\u0131 i\u00e7in grup ad\u0131 “A” olan gruba ait t\u00fcm sat\u0131rlar\u0131 d\u00f6nd\u00fcrd\u00fc\u011f\u00fcn\u00fc unutmay\u0131n.<\/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 Pandalarda GroupBy toplam\u0131 nas\u0131l ger\u00e7ekle\u015ftirilir?<\/a> Bir pandan\u0131n DataFrame’inde groupby() i\u015flevini kulland\u0131ktan sonra belirli bir grubu elde etmek i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemleri kullanabilirsiniz: Y\u00f6ntem 1: groupby()’yi kulland\u0131ktan sonra grubu al\u0131n grouped_df. get_group (‘ A ‘) Y\u00f6ntem 2: Groupby()’yi kulland\u0131ktan sonra gruptan belirli s\u00fctunlar\u0131 al\u0131n grouped_df[[‘ column1 ‘, ‘ column3 ‘]]. get_group (‘ A ‘) A\u015fa\u011f\u0131daki \u00f6rnekler, her y\u00f6ntemin pratikte a\u015fa\u011f\u0131daki pandalar DataFrame […]<\/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-3766","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n grouped_df. get_group<\/span> (' A<\/span> ')\n<\/strong><\/pre>\n grouped_df[[' column1<\/span> ', ' column3<\/span> ']]. get_group<\/span> (' A<\/span> ')<\/strong><\/pre>\n import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' store<\/span> ': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],\n ' sales<\/span> ': [12, 15, 24, 24, 14, 19, 12, 38],\n ' refunds<\/span> ': [4, 8, 7, 7, 10, 5, 4, 11]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n store sales refunds\n0 to 12 4\n1 to 15 8\n2 to 24 7\n3 to 24 7\n4 B 14 10\n5 B 19 5\n6 B 12 4\n7 B 38 11<\/b><\/pre>\n \u00d6rnek 1: groupby() kulland\u0131ktan sonra bir grup edinin<\/strong><\/span><\/h2>\n
#group rows of DataFrame based on value in 'store' column\ngrouped_stores = df. groupby<\/span> ([' store<\/span> '])\n\n#get all rows that belong to group name 'A'\n<\/span>grouped_stores. get_group<\/span> (' A<\/span> ')\n\n store sales refunds\n0 to 12 4\n1 to 15 8\n2 to 24 7\n3 to 24 7\n<\/span><\/span><\/strong><\/pre>\n \u00d6rnek 2: groupby()’yi kulland\u0131ktan sonra gruptan belirli s\u00fctunlar\u0131 al\u0131n<\/strong><\/span><\/h2>\n
#group rows of DataFrame based on value in 'store' column\ngrouped_stores = df. groupby<\/span> ([' store<\/span> '])\n\n#get all rows that belong to group name 'A' for sales and refunds columns\n<\/span>grouped_stores[[' store<\/span> ', ' refunds<\/span> ']]. get_group<\/span> (' A<\/span> ')\n\n store refunds\n0 to 4\n1 to 8\n2 to 7\n3 to 7\n<\/span><\/span><\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
Pandalarda Groupby ve Plot nas\u0131l kullan\u0131l\u0131r?<\/a>
Pandalar’da GroupBy kullan\u0131larak benzersiz de\u011ferler nas\u0131l say\u0131l\u0131r?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"