{"id":2408,"date":"2023-07-22T10:02:37","date_gmt":"2023-07-22T10:02:37","guid":{"rendered":"https:\/\/statorials.org\/tr\/pandalarin-bahce-sutunlari\/"},"modified":"2023-07-22T10:02:37","modified_gmt":"2023-07-22T10:02:37","slug":"pandalarin-bahce-sutunlari","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/pandalarin-bahce-sutunlari\/","title":{"rendered":"Pandalarda baz\u0131 s\u00fctunlar nas\u0131l korunur (\u00f6rneklerle)"},"content":{"rendered":"

<\/p>\n

\n

Bir pandas DataFrame’de yaln\u0131zca belirli s\u00fctunlar\u0131 kal\u0131c\u0131 k\u0131lmak i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemleri kullanabilirsiniz:<\/span><\/p>\n

Y\u00f6ntem 1: Hangi s\u00fctunlar\u0131n tutulaca\u011f\u0131n\u0131 belirtme<\/strong><\/span><\/p>\n

 #only keep columns 'col1' and 'col2'<\/span>\ndf[[' col1<\/span> ', ' col2<\/span> ']]\n<\/strong><\/pre>\n
 Y\u00f6ntem 2: Silinecek s\u00fctunlar\u0131 belirtme<\/strong><\/span><\/p>\n
 #drop columns 'col3' and 'col4'<\/span>\ndf[df. columns<\/span> [~df. columns<\/span> . isin<\/span> ([' col3<\/span> ',' col4<\/span> '])]]\n<\/strong><\/pre>\n
 A\u015fa\u011f\u0131daki \u00f6rnekler, her y\u00f6ntemin 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\n<\/span>df = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'B', 'B', 'B'],\n                   ' points<\/span> ': [11, 7, 8, 10, 13, 13],\n                   ' assists<\/span> ': [5, 7, 7, 9, 12, 9],\n                   ' rebounds<\/span> ': [11, 8, 10, 6, 6, 5]})\n\n<\/span>#view DataFrame\n<\/span><\/span>df\n\n\tteam points assists rebounds\n0 A 11 5 11\n1 To 7 7 8\n2 to 8 7 10\n3 B 10 9 6\n4 B 13 12 6\n5 B 13 9 5\n<\/span><\/span><\/strong><\/pre>\n
 Y\u00f6ntem 1: Hangi s\u00fctunlar\u0131n tutulaca\u011f\u0131n\u0131 belirtme<\/strong><\/span><\/h3>\n
 A\u015fa\u011f\u0131daki kod, yaln\u0131zca “ekip” ve “puan” s\u00fctunlar\u0131n\u0131 tutan yeni bir DataFrame’in nas\u0131l tan\u0131mlanaca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n
 #create new DataFrame and only keep 'team' and 'points' columns\n<\/span>df2 = df[[' team<\/span> ', ' points<\/span> ']]\n\n#view new DataFrame\n<\/span>df2\n\n        team points\n0 to 11\n1 to 7\n2 to 8\n3 B 10\n4 B 13\n5 B 13<\/span><\/span><\/strong><\/pre>\n
 Ortaya \u00e7\u0131kan DataFrame’in yaln\u0131zca belirtti\u011fimiz iki s\u00fctunu korudu\u011funu unutmay\u0131n.<\/span><\/p>\n
 Y\u00f6ntem 2: Silinecek s\u00fctunlar\u0131 belirtme<\/strong><\/span><\/h3>\n
 A\u015fa\u011f\u0131daki kod, orijinal DataFrame’den “kat\u0131l\u0131r” ve “geri d\u00f6ner” s\u00fctunlar\u0131n\u0131 kald\u0131ran yeni bir DataFrame’in nas\u0131l tan\u0131mlanaca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n
 #create new DataFrame and that drops 'assists' and 'rebounds'\n<\/span>df2 = df[df. columns<\/span> [~df. columns<\/span> . isin<\/span> ([' assists<\/span> ', ' rebounds<\/span> '])]]\n\n#view new DataFrame\n<\/span>df2\n\n        team points\n0 to 11\n1 to 7\n2 to 8\n3 B 10\n4 B 13\n5 B 13<\/span><\/span><\/strong><\/pre>\n
 Ortaya \u00e7\u0131kan DataFrame’in orijinal DataFrame’den “destek” ve “geri d\u00f6nen” s\u00fctunlar\u0131n\u0131 kald\u0131rd\u0131\u011f\u0131n\u0131 ve kalan s\u00fctunlar\u0131 korudu\u011funu unutmay\u0131n.<\/span><\/p>\n
 Ek kaynaklar<\/strong><\/span><\/h3>\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
 Pandas DataFrame’deki ilk s\u00fctun nas\u0131l kald\u0131r\u0131l\u0131r<\/a>
 Pandalar’da yinelenen s\u00fctunlar nas\u0131l kald\u0131r\u0131l\u0131r<\/a>
 Pandalar’da s\u00fctunlar\u0131 dizine g\u00f6re nas\u0131l silebilirim?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
Bir pandas DataFrame’de yaln\u0131zca belirli s\u00fctunlar\u0131 kal\u0131c\u0131 k\u0131lmak i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemleri kullanabilirsiniz: Y\u00f6ntem 1: Hangi s\u00fctunlar\u0131n tutulaca\u011f\u0131n\u0131 belirtme #only keep columns ‘col1’ and ‘col2’ df[[‘ col1 ‘, ‘ col2 ‘]] Y\u00f6ntem 2: Silinecek s\u00fctunlar\u0131 belirtme #drop columns ‘col3’ and ‘col4’ df[df. columns [~df. columns . isin ([‘ col3 ‘,’ col4 ‘])]] A\u015fa\u011f\u0131daki \u00f6rnekler, her y\u00f6ntemin […]<\/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-2408","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\nPandalarda belirli s\u00fctunlar nas\u0131l korunur (\u00f6rneklerle) \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"Bu e\u011fitimde, bir 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