{"id":4154,"date":"2023-07-13T05:53:17","date_gmt":"2023-07-13T05:53:17","guid":{"rendered":"https:\/\/statorials.org\/tr\/pandalarin-histogram-yuzdesi\/"},"modified":"2023-07-13T05:53:17","modified_gmt":"2023-07-13T05:53:17","slug":"pandalarin-histogram-yuzdesi","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/pandalarin-histogram-yuzdesi\/","title":{"rendered":"Pandalar histogram\u0131n\u0131n y ekseninde y\u00fczde nas\u0131l g\u00f6r\u00fcnt\u00fclenir?"},"content":{"rendered":"

<\/p>\n

\n

Bir panda histogram\u0131n\u0131n y eksenindeki y\u00fczdeleri g\u00f6r\u00fcnt\u00fclemek i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n

 import<\/span> pandas as<\/span> pd\nimport<\/span> numpy as<\/span> np\nimport<\/span> matplotlib. pyplot<\/span> as<\/span> plt\nfrom<\/span> matplotlib. ticker<\/span> import<\/span> PercentFormatter\n\n#create histogram, using percentages instead of counts<\/span>\nplt. hist<\/span> (df[' my_column<\/span> '], weights= np.ones<\/span> ( len<\/span> (df)) \/ len<\/span> (df))\n\n#apply percentage format to y-axis\n<\/span>plt. gca<\/span> (). yaxis<\/span> . set_major_formatter<\/span> (PercentFormatter(1))\nplt. show<\/span> ()\n<\/strong><\/pre>\n
 A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n
 \u00d6rnek: Panda histogram\u0131n\u0131n Y ekseninde y\u00fczdeyi g\u00f6ster<\/strong><\/span><\/h2>\n
 \u00c7e\u015fitli basketbol oyuncular\u0131 hakk\u0131nda bilgi i\u00e7eren a\u015fa\u011f\u0131daki pandalar DataFrame’e sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\nimport<\/span> numpy as<\/span> np\n\n#make this example reproducible\n<\/span>n.p. random<\/span> . seeds<\/span> (1)\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' points<\/span> ': np. random<\/span> . normal<\/span> (loc=20, scale=2, size=300),\n                   ' assists<\/span> ': np. random<\/span> . normal<\/span> (loc=14, scale=3, size=300),\n                   ' rebounds<\/span> ': np. random<\/span> . normal<\/span> (loc=12, scale=1, size=300)})\n\n#view head of DataFrame\n<\/span>print<\/span> ( df.head<\/span> ())\n\n      points assists rebounds\n0 23.248691 20.197350 10.927036\n1 18.776487 9.586529 12.495159\n2 18.943656 11.509484 11.047938\n3 17.854063 11.358267 11.481854\n4 21.730815 13.162707 10.538596\n<\/span><\/span><\/strong><\/pre>\n
 Puan<\/strong> s\u00fctunundaki de\u011ferlerin da\u011f\u0131l\u0131m\u0131n\u0131 g\u00f6rselle\u015ftirmek i\u00e7in bir histogram olu\u015fturursak, y ekseni varsay\u0131lan olarak say\u0131lar\u0131 g\u00f6sterecektir:<\/span> <\/p>\n
 import<\/span> matplotlib. pyplot<\/span> as<\/span> plt \n\n#create histogram for points columb\n<\/span>plt. hist<\/span> (df[' points<\/span> '], edgecolor=' black<\/span> ')\n<\/span><\/span><\/strong><\/pre>\n
\"\"<\/p>\n
 Y\u00fczdeleri y ekseninde g\u00f6r\u00fcnt\u00fclemek i\u00e7in PercentFormatter<\/strong> i\u015flevini kullanabiliriz:<\/span> <\/p>\n
 import<\/span> numpy as<\/span> np\nimport<\/span> matplotlib. pyplot<\/span> as<\/span> plt\nfrom<\/span> matplotlib. ticker<\/span> import<\/span> PercentFormatter\n\n#create histogram, using percentages instead of counts<\/span>\nplt. hist<\/span> (df[' points<\/span> '], weights=np. ones<\/span> ( len<\/span> (df)) \/ len<\/span> (df), edgecolor=' black<\/span> ')\n\n#apply percentage format to y-axis\n<\/span>plt. gca<\/span> (). yaxis<\/span> . set_major_formatter<\/span> (PercentFormatter(1))\nplt. show<\/span> ()<\/strong> <\/pre>\n
\"y<\/p>\n
 Y ekseninin art\u0131k y\u00fczdeleri g\u00f6r\u00fcnt\u00fcledi\u011fini unutmay\u0131n.<\/span><\/p>\n
 Y\u00fczdelerden ondal\u0131k basamaklar\u0131 kald\u0131rmak istiyorsan\u0131z PercentFormatter()<\/strong> i\u015flevinde decimals=0<\/strong> ba\u011f\u0131ms\u0131z de\u011fi\u015fkenini kullanman\u0131z yeterlidir:<\/span> <\/p>\n
 import<\/span> numpy as<\/span> np\nimport<\/span> matplotlib. pyplot<\/span> as<\/span> plt\nfrom<\/span> matplotlib. ticker<\/span> import<\/span> PercentFormatter\n\n#create histogram, using percentages instead of counts<\/span>\nplt. hist<\/span> (df[' points<\/span> '], weights=np. ones<\/span> ( len<\/span> (df)) \/ len<\/span> (df), edgecolor=' black<\/span> ')\n\n#apply percentage format to y-axis\n<\/span>plt. gca<\/span> (). yaxis<\/span> . set_major_formatter<\/span> (PercentFormatter(1, decimals= 0<\/span> ))\nplt. show<\/span> ()<\/strong> <\/pre>\n
\"Pandalar<\/p>\n
 Y ekseni art\u0131k ondal\u0131k basamak olmadan y\u00fczdeleri g\u00f6steriyor.<\/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
 Panda’n\u0131n histogram\u0131nda kullan\u0131lan kutu say\u0131s\u0131 nas\u0131l de\u011fi\u015ftirilir?<\/a>
 Pandalar histogram\u0131nda X ekseni aral\u0131\u011f\u0131 nas\u0131l de\u011fi\u015ftirilir?<\/a>
 Pandalarda histogramlar gruba g\u00f6re nas\u0131l \u00e7izilir?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
Bir panda histogram\u0131n\u0131n y eksenindeki y\u00fczdeleri g\u00f6r\u00fcnt\u00fclemek i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz: import pandas as pd import numpy as np import matplotlib. pyplot as plt from matplotlib. ticker import PercentFormatter #create histogram, using percentages instead of counts plt. hist (df[‘ my_column ‘], weights= np.ones ( len (df)) \/ len (df)) #apply percentage format to y-axis […]<\/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-4154","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\nPanda histogram\u0131n\u0131n Y ekseninde y\u00fczde nas\u0131l g\u00f6sterilir?<\/title>\n<meta name=\"description\" content=\"Bu e\u011fitimde bir panda histogram\u0131n\u0131n y ekseninde y\u00fczdelerin nas\u0131l 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