{"id":4262,"date":"2023-07-12T11:08:26","date_gmt":"2023-07-12T11:08:26","guid":{"rendered":"https:\/\/statorials.org\/tr\/deniz-dogusu-cift-grafigi-renk-tonu\/"},"modified":"2023-07-12T11:08:26","modified_gmt":"2023-07-12T11:08:26","slug":"deniz-dogusu-cift-grafigi-renk-tonu","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/deniz-dogusu-cift-grafigi-renk-tonu\/","title":{"rendered":"Seaborn: pairplot'ta renk tonu parametresi nas\u0131l kullan\u0131l\u0131r?"},"content":{"rendered":"

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Belirli bir de\u011fi\u015fkenin de\u011ferlerine g\u00f6re grafi\u011fin y\u00f6nlerini renklendirmek i\u00e7in Seaborn’da \u00e7izim \u00e7iftleri olu\u015ftururken renk tonu<\/strong> parametresini kullanabilirsiniz.<\/span><\/p>\n

A\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n

 import<\/span> seaborn as<\/span> sns\n\nsns. pairplot<\/span> (data=df, hue=' team<\/span> ')\n<\/strong><\/pre>\n
 Bu \u00f6zel \u00f6rnek, veri \u00e7er\u00e7evesindeki her bir say\u0131sal de\u011fi\u015fkeni ve tak\u0131m<\/strong> de\u011fi\u015fkeninin de\u011ferine ba\u011fl\u0131 olarak \u00e7izimin renk \u00f6zelliklerini kullanarak bir \u00e7ift \u00e7izimi olu\u015fturur.<\/span><\/p>\n
 A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n
 \u00d6rnek: Seaborn Pairplot’ta Hue Parametresini Kullanmak<\/strong><\/span><\/h2>\n
 \u0130ki farkl\u0131 tak\u0131mdaki basketbolcular\u0131n say\u0131lar\u0131n\u0131 ve asistlerini g\u00f6steren a\u015fa\u011f\u0131daki panda DataFrame’e sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'A', 'A', 'B', 'B', 'B', 'B', 'B'],\n                   ' assists<\/span> ': [3, 4, 4, 7, 9, 6, 7, 8, 10, 12],\n                   ' points<\/span> ': [5, 6, 9, 12, 15, 5, 10, 13, 13, 19]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  team assists points\n0 to 3 5\n1 to 4 6\n2 to 4 9\n3 to 7 12\n4 to 9 15\n5 B 6 5\n6 B 7 10\n7 B 8 13\n8 B 10 13\n9 B 12 19\n<\/strong><\/span><\/pre>\n
 Pairplot()<\/strong> i\u015flevini kullan\u0131rsak, Seaborn, DataFrame’deki iki say\u0131sal de\u011fi\u015fkeni kullanarak bir \u00e7ift grafi\u011fi olu\u015fturacakt\u0131r:<\/span> <\/p>\n
 import<\/span> seaborn as<\/span> sns\n\n#create pairplot\n<\/span>sns. pairplot<\/span> (data=df)<\/strong><\/span> <\/pre>\n
\"\"<\/p>\n
 Ortaya \u00e7\u0131kan \u00e7ift grafi\u011fi, noktalar\u0131 ve yard\u0131mc\u0131 de\u011fi\u015fkenleri kullanarak da\u011f\u0131l\u0131m grafiklerini ve histogramlar\u0131 g\u00f6r\u00fcnt\u00fcler.<\/span><\/p>\n
 Pairplot()<\/strong> i\u015flevinde hue<\/strong> parametresini kullan\u0131rsak, tak\u0131m<\/strong> de\u011fi\u015fkeninin de\u011ferlerine g\u00f6re \u00e7izimin baz\u0131 y\u00f6nlerini renklendirebiliriz:<\/span> <\/p>\n
 import<\/span> seaborn as<\/span> sns\n\n#create pairplot using values of team variable as colors\n<\/span>sns. pairplot<\/span> (data=df, hue=' team<\/span> ')<\/strong><\/span> <\/pre>\n
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 Hue<\/strong> parametresini kullanarak \u00e7izimde a\u015fa\u011f\u0131daki de\u011fi\u015fiklikleri yapabiliriz:<\/span><\/span><\/p>\n