{"id":3803,"date":"2023-07-15T11:15:50","date_gmt":"2023-07-15T11:15:50","guid":{"rendered":"https:\/\/statorials.org\/tr\/pandalar-satirlari-veya-iki-sutunun-esit-oldugunu-secer\/"},"modified":"2023-07-15T11:15:50","modified_gmt":"2023-07-15T11:15:50","slug":"pandalar-satirlari-veya-iki-sutunun-esit-oldugunu-secer","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/pandalar-satirlari-veya-iki-sutunun-esit-oldugunu-secer\/","title":{"rendered":"Pandalar: iki s\u00fctunun e\u015fit oldu\u011fu sat\u0131rlar\u0131 se\u00e7in"},"content":{"rendered":"

<\/p>\n

\n

Pandas DataFrame’de iki s\u00fctunun e\u015fit oldu\u011fu (veya e\u015fit olmad\u0131\u011f\u0131) sat\u0131rlar\u0131 se\u00e7mek i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemleri kullanabilirsiniz:<\/span><\/p>\n

Y\u00f6ntem 1: \u0130ki s\u00fctunun e\u015fit oldu\u011fu sat\u0131rlar\u0131 se\u00e7in<\/strong><\/span><\/p>\n

 df. query<\/span> (' column1 ==column2<\/span> ')\n<\/strong><\/pre>\n
 Y\u00f6ntem 2: \u0130ki s\u00fctunun e\u015fit olmad\u0131\u011f\u0131 sat\u0131rlar\u0131 se\u00e7in<\/strong><\/span><\/p>\n
 df. query<\/span> (' column1<\/span> !=column2<\/span> ')<\/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> ({' painting<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F'],\n                   ' fail1<\/span> ': ['Good', 'Good', 'Bad', 'Bad', 'Good', 'Good'],\n                   ' fail2<\/span> ': ['Good', 'Bad', 'Bad', 'Good', 'Good', 'Good']})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  painting rater1 rater2\n0 A Good Good\n1 B Good Bad\n2 C Bad Bad\n3 D Bad Good\n4 E Good Good\n5 F Good Good<\/strong><\/pre>\n
 \u00d6rnek 1: \u0130ki s\u00fctunun e\u015fit oldu\u011fu sat\u0131rlar\u0131 se\u00e7in<\/strong><\/span><\/h2>\n
 DataFrame’de yaln\u0131zca rater1<\/strong> ve rater2<\/strong> s\u00fctunlar\u0131n\u0131n de\u011ferlerinin e\u015fit oldu\u011fu sat\u0131rlar\u0131 se\u00e7mek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabiliriz:<\/span><\/p>\n
 #select rows where rater1 is equal to rater2\n<\/span>df. query<\/span> (' rater1 ==rater2<\/span> ')\n\n painting rater1 rater2\n0 A Good Good\n2 C Bad Bad\n4 E Good Good\n5 F Good Good<\/strong><\/pre>\n
 Yaln\u0131zca miss1<\/strong> ve miss2’nin<\/strong> e\u015fit oldu\u011fu sat\u0131rlar\u0131n se\u00e7ildi\u011fini unutmay\u0131n.<\/span><\/span><\/p>\n
 Rater1<\/strong> ve rater2<\/strong> s\u00fctunlar\u0131nda ka\u00e7 sat\u0131r\u0131n e\u015fit de\u011fere sahip oldu\u011funu saymak istersek len()<\/strong> fonksiyonunu da kullanabiliriz:<\/span><\/span><\/p>\n
 #count the number of rows where rater1 is equal to rater2\n<\/span>len<\/span> ( df.query<\/span> (' rater1 ==rater2<\/span> '))\n\n4<\/strong><\/pre>\n
 Bu bize miss1<\/strong> ve miss2<\/strong> s\u00fctunlar\u0131n\u0131n de\u011ferlerinin e\u015fit oldu\u011fu 4<\/strong> sat\u0131r oldu\u011funu s\u00f6yler.<\/span><\/p>\n
 \u00d6rnek 2: \u0130ki s\u00fctunun e\u015fit olmad\u0131\u011f\u0131 sat\u0131rlar\u0131 se\u00e7in<\/strong><\/span><\/h2>\n
 DataFrame’de yaln\u0131zca de\u011ferlendirici1<\/strong> ve de\u011ferlendirici2<\/strong> s\u00fctunlar\u0131n\u0131n de\u011ferlerinin e\u015fit olmad\u0131\u011f\u0131 sat\u0131rlar\u0131 se\u00e7mek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabiliriz:<\/span><\/p>\n
 #select rows where rater1 is not equal to rater2\n<\/span>df. query<\/span> (' rater1 !=rater2<\/span> ')\n\n painting rater1 rater2\n1 B Good Bad\n3 D Bad Good<\/strong><\/pre>\n
 Yaln\u0131zca miss1<\/strong> ve miss2’nin<\/strong> e\u015fit olmad\u0131\u011f\u0131 sat\u0131rlar\u0131n se\u00e7ildi\u011fini unutmay\u0131n.<\/span><\/p>\n
 Ek kaynaklar<\/strong><\/span><\/h2>\n
 A\u015fa\u011f\u0131daki e\u011fitimlerde pandalarda di\u011fer ortak g\u00f6revlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n
 Pandalar’da s\u00fctunlar nas\u0131l yeniden adland\u0131r\u0131l\u0131r?<\/a>
 Pandas DataFrame’e s\u00fctun nas\u0131l eklenir
 Pandas DataFrame’de s\u00fctun s\u0131ras\u0131 nas\u0131l de\u011fi\u015ftirilir?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
Pandas DataFrame’de iki s\u00fctunun e\u015fit oldu\u011fu (veya e\u015fit olmad\u0131\u011f\u0131) sat\u0131rlar\u0131 se\u00e7mek i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemleri kullanabilirsiniz: Y\u00f6ntem 1: \u0130ki s\u00fctunun e\u015fit oldu\u011fu sat\u0131rlar\u0131 se\u00e7in df. query (‘ column1 ==column2 ‘) Y\u00f6ntem 2: \u0130ki s\u00fctunun e\u015fit olmad\u0131\u011f\u0131 sat\u0131rlar\u0131 se\u00e7in df. query (‘ column1 !=column2 ‘) 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: […]<\/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-3803","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\nPandalar: iki s\u00fctunun e\u015fit oldu\u011fu sat\u0131rlar\u0131 se\u00e7in - 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