{"id":2238,"date":"2023-07-23T03:16:00","date_gmt":"2023-07-23T03:16:00","guid":{"rendered":"https:\/\/statorials.org\/tr\/deniz-alt-alanlari\/"},"modified":"2023-07-23T03:16:00","modified_gmt":"2023-07-23T03:16:00","slug":"deniz-alt-alanlari","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/deniz-alt-alanlari\/","title":{"rendered":"Seaborn'da alt konular nas\u0131l olu\u015fturulur (\u00f6rneklerle)"},"content":{"rendered":"

<\/p>\n

\n

Python’daki Seaborn<\/a> veri g\u00f6rselle\u015ftirme kitapl\u0131\u011f\u0131nda alt grafikler olu\u015fturmak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n

 #define dimensions of subplots (rows, columns)\n<\/span>fig, axes = plt. subplots<\/span> (2, 2)\n\n#create chart in each subplot\n<\/span>sns. boxplot<\/span> (data=df, x=' team<\/span> ', y=' points<\/span> ', ax=axes[0,0])\nsns. boxplot<\/span> (data=df, x=' team<\/span> ', y=' assists<\/span> ', ax=axes[0,1])\n\n...\n<\/strong><\/span><\/pre>\n
 A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n
 \u00d6rnek: Seaborn’da Alt Grafikler Olu\u015fturma<\/strong><\/span><\/h3>\n
 A\u015fa\u011f\u0131daki pandalara sahip oldu\u011fumuzu varsayal\u0131m DataFrame:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],\n                   ' points<\/span> ': [19, 12, 15, 14, 19, 23, 25, 29],\n                   ' assists<\/span> ': [13, 15, 11, 8, 6, 8, 11, 14],\n                   ' rebounds<\/span> ': [11, 7, 8, 12, 13, 7, 6, 8],\n                   ' blocks<\/span> ': [1, 2, 2, 3, 5, 4, 3, 3]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  team points assists rebounds blocks\n0 A 19 13 11 1\n1 A 12 15 7 2\n2 A 15 11 8 2\n3 A 14 8 12 3\n4 B 19 6 13 5\n5 B 23 8 7 4\n6 B 25 11 6 3\n7 B 29 14 8 3<\/span><\/span><\/strong><\/pre>\n
 A\u015fa\u011f\u0131daki kod, iki sat\u0131r ve iki s\u00fctunlu bir \u00e7izim b\u00f6lgesinin nas\u0131l tan\u0131mlanaca\u011f\u0131n\u0131 ve DataFrame’deki d\u00f6rt say\u0131sal de\u011fi\u015fkenin her biri i\u00e7in her alt grafikte bir kutu grafi\u011finin nas\u0131l olu\u015fturulaca\u011f\u0131n\u0131 g\u00f6sterir:<\/span> <\/p>\n
 import<\/span> matplotlib.<\/b><\/span> pyplot<\/span> <\/b>as<\/span> plt\n<\/b><\/span>import<\/span> seaborn<\/b><\/span> as<\/span> sns\n\n#set seaborn plotting aesthetics as default<\/span>\n<\/b><\/span>sns.<\/b><\/span> set<\/span> ()\n\n#define plotting region (2 rows, 2 columns)\n<\/span>fig, axes = plt.<\/b><\/span> subplots<\/span> (2, 2)\n\n<\/b><\/span>#create boxplot in each subplot\n<\/span>sns. boxplot<\/span> (data=df, x=' team<\/span> ', y=' points<\/span> ', ax=axes[0,0])\nsns. boxplot<\/span> (data=df, x=' team<\/span> ', y=' assists<\/span> ', ax=axes[0,1])\nsns. boxplot<\/span> (data=df, x=' team<\/span> ', y=' rebounds<\/span> ', ax=axes[1,0])\nsns. boxplot<\/span> (data=df, x=' team<\/span> ', y=' blocks<\/span> ', ax=axes[1,1])\n<\/b><\/span><\/pre>\n
\"Python'daki<\/p>\n
 Bu \u00f6rnekte iki sat\u0131r ve iki s\u00fctundan olu\u015fan bir \u00e7izim b\u00f6lgesi olu\u015fturduk ve her alt grafi\u011fi kutu grafikleriyle doldurduk.<\/span><\/p>\n
 Ancak farkl\u0131 boyutlara sahip bir \u00e7izim b\u00f6lgesi olu\u015fturmak ve alt grafikleri farkl\u0131 grafiklerle doldurmak i\u00e7in benzer s\u00f6zdizimini kullanabiliriz.<\/span><\/p>\n
 \u00d6rne\u011fin, a\u015fa\u011f\u0131daki kod, bir sat\u0131r ve iki s\u00fctunlu bir \u00e7izim b\u00f6lgesinin nas\u0131l olu\u015fturulaca\u011f\u0131n\u0131 ve her grafi\u011fin bir keman grafi\u011fiyle nas\u0131l doldurulaca\u011f\u0131n\u0131 g\u00f6sterir:<\/span> <\/p>\n
 import<\/span> matplotlib.<\/b><\/span> pyplot<\/span> <\/b>as<\/span> plt\n<\/b><\/span>import<\/span> seaborn<\/b><\/span> as<\/span> sns\n\n#set seaborn plotting<\/span><\/b><\/span> aesthetics<\/b><\/span><\/span> as default\n<\/span>sns.<\/b><\/span> set<\/span> ()\n\n#define plotting region (1 row, 2 columns)\n<\/span>fig, axes = plt.<\/b><\/span> subplots<\/span> (1, 2)\n\n<\/b><\/span>#create boxplot in each subplot\n<\/span>sns. violinplot<\/span> (data=df, x=' team<\/span> ', y=' points<\/span> ', ax=axes[0])\nsns. violinplot<\/span> (data=df, x=' team<\/span> ', y=' assists<\/span> ', ax=axes[1])\n<\/b><\/span><\/pre>\n
\"\"<\/p>\n
 Ek kaynaklar<\/strong><\/span><\/h3>\n
 A\u015fa\u011f\u0131daki e\u011fitimler, deniz do\u011fu\u015funda di\u011fer ortak i\u015flevlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fini a\u00e7\u0131klamaktad\u0131r:<\/span><\/p>\n
 Seaborn Arsalar\u0131na Ba\u015fl\u0131k Nas\u0131l Eklenir?<\/a>
 Seaborn grafi\u011fini bir dosyaya nas\u0131l kaydederim?
 Seaborn’da bir efsanenin konumu nas\u0131l de\u011fi\u015ftirilir?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
Python’daki Seaborn veri g\u00f6rselle\u015ftirme kitapl\u0131\u011f\u0131nda alt grafikler olu\u015fturmak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz: #define dimensions of subplots (rows, columns) fig, axes = plt. subplots (2, 2) #create chart in each subplot sns. boxplot (data=df, x=’ team ‘, y=’ points ‘, ax=axes[0,0]) sns. boxplot (data=df, x=’ team ‘, y=’ assists ‘, ax=axes[0,1]) … 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-2238","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\nSeaborn'da Alt Konular Nas\u0131l Olu\u015fturulur (\u00d6rneklerle) \u2013 Statoryaller<\/title>\n<meta name=\"description\" content=\"Bu e\u011fitimde Seaborn'da alt grafiklerin nas\u0131l 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