<\/p>\n
Bir DataFrame’in belirli bir s\u00fctunundaki de\u011ferlerin olu\u015fumlar\u0131n\u0131 saymak i\u00e7in pandalarda value_counts()<\/strong> i\u015flevini kullanabilirsiniz.<\/span><\/p>\n value_counts()<\/strong> i\u015flevinin sonu\u00e7lar\u0131n\u0131 s\u0131ralamak i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemlerden birini kullanabilirsiniz:<\/span><\/p>\n Y\u00f6ntem 1: Hesaplar\u0131 azalan d\u00fczende s\u0131ralay\u0131n (varsay\u0131lan)<\/strong><\/span><\/p>\n Y\u00f6ntem 2: Hesaplar\u0131 artan d\u00fczende s\u0131ralay\u0131n<\/strong><\/span><\/p>\n Y\u00f6ntem 3: Say\u0131lar\u0131 DataFrame’de g\u00f6r\u00fcnd\u00fckleri s\u0131raya g\u00f6re s\u0131ralay\u0131n<\/strong><\/span><\/p>\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 A\u015fa\u011f\u0131daki kod, ekip s\u00fctunundaki her benzersiz de\u011ferin olu\u015fumlar\u0131n\u0131n nas\u0131l say\u0131laca\u011f\u0131n\u0131 ve say\u0131lar\u0131n azalan d\u00fczende nas\u0131l s\u0131ralanaca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n Say\u0131mlar\u0131n varsay\u0131lan olarak azalan d\u00fczende s\u0131raland\u0131\u011f\u0131n\u0131 unutmay\u0131n.<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, ekip s\u00fctunundaki her benzersiz de\u011ferin olu\u015fumlar\u0131n\u0131n nas\u0131l say\u0131laca\u011f\u0131n\u0131 ve say\u0131lar\u0131n artan d\u00fczende nas\u0131l s\u0131ralanaca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n Hesaplar\u0131n art\u0131k artan d\u00fczende, yani en k\u00fc\u00e7\u00fckten en b\u00fcy\u00fc\u011fe do\u011fru s\u0131raland\u0131\u011f\u0131n\u0131 unutmay\u0131n.<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, ekip s\u00fctunundaki her benzersiz de\u011ferin olu\u015fumunun nas\u0131l say\u0131laca\u011f\u0131n\u0131 ve say\u0131lar\u0131n, benzersiz de\u011ferlerin DataFrame’de g\u00f6r\u00fcnd\u00fc\u011f\u00fc s\u0131raya g\u00f6re nas\u0131l s\u0131ralanaca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n Say\u0131mlar\u0131n art\u0131k benzersiz de\u011ferlerin DataFrame’de g\u00f6r\u00fcnme s\u0131ras\u0131na g\u00f6re s\u0131raland\u0131\u011f\u0131n\u0131 unutmay\u0131n.<\/span><\/p>\n \u00d6rne\u011fin, tak\u0131m s\u00fctununda \u00f6nce “A” de\u011feri g\u00f6r\u00fcn\u00fcr, ard\u0131ndan “B” ve ard\u0131ndan “C” g\u00f6r\u00fcn\u00fcr.<\/span><\/p>\n Bu, \u00e7\u0131kt\u0131da say\u0131mlar\u0131n g\u00f6r\u00fcnme s\u0131ras\u0131d\u0131r.<\/span><\/p>\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: de\u011fer hesaplar\u0131n\u0131n grafi\u011fi nas\u0131l \u00e7izilir<\/a> Bir DataFrame’in belirli bir s\u00fctunundaki de\u011ferlerin olu\u015fumlar\u0131n\u0131 saymak i\u00e7in pandalarda value_counts() i\u015flevini kullanabilirsiniz. value_counts() i\u015flevinin sonu\u00e7lar\u0131n\u0131 s\u0131ralamak i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemlerden birini kullanabilirsiniz: Y\u00f6ntem 1: Hesaplar\u0131 azalan d\u00fczende s\u0131ralay\u0131n (varsay\u0131lan) df. my_column . value_counts () Y\u00f6ntem 2: Hesaplar\u0131 artan d\u00fczende s\u0131ralay\u0131n df. my_column . value_counts (). sort_values () Y\u00f6ntem 3: Say\u0131lar\u0131 DataFrame’de g\u00f6r\u00fcnd\u00fckleri s\u0131raya g\u00f6re s\u0131ralay\u0131n […]<\/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-3950","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n df. my_column<\/span> . value_counts<\/span> ()<\/strong><\/pre>\n df. my_column<\/span> . value_counts<\/span> (). sort_values<\/span> ()<\/strong><\/pre>\n df. my_column<\/span> . value_counts<\/span> ()[df. my_column<\/span> . single<\/span> ()]<\/strong><\/pre>\n import<\/span> pandas as<\/span> pd\n\n#createDataFrame\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'B', 'B', 'B', 'B', 'B', 'C'],\n ' points<\/span> ': [15, 12, 18, 20, 22, 28, 35, 40]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n team points\n0 to 15\n1 to 12\n2 B 18\n3 B 20\n4 B 22\n5 B 28\n6 B 35\n7 C 40\n<\/span><\/span><\/strong><\/pre>\n \u00d6rnek 1: Hesaplar\u0131 azalan d\u00fczende s\u0131ralay\u0131n<\/strong><\/span><\/h2>\n
#count occurrences of each value in team column and sort in descending order\n<\/span>df. team<\/span> . value_counts<\/span> ()\n\nB5\nAt 2\nC 1\nName: team, dtype: int64\n<\/strong><\/pre>\n \u00d6rnek 2: Hesaplar\u0131 artan d\u00fczende s\u0131ralay\u0131n<\/strong><\/span><\/h2>\n
#count occurrences of each value in team column and sort in ascending order\n<\/span>df. team<\/span> . value_counts<\/span> (). sort_values<\/span> ()\n\nC 1\nAt 2\nB5\nName: team, dtype: int64\n<\/strong><\/pre>\n \u00d6rnek 3: Hesaplar\u0131 DataFrame’de g\u00f6r\u00fcnd\u00fckleri s\u0131raya g\u00f6re s\u0131ralay\u0131n<\/strong><\/span><\/h2>\n
#count occurrences of each value in team column and sort in order they appear\n<\/span>df. team<\/span> . value_counts<\/span> ()[df. team<\/span> . single<\/span> ()]\n\nAt 2\nB5\nC 1\nName: team, dtype: int64\n<\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
Pandalar: GroupBy ve de\u011fer say\u0131lar\u0131 nas\u0131l kullan\u0131l\u0131r?<\/a>
Pandalar: value_counts’un y\u00fczde olarak nas\u0131l temsil edilece\u011fi<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"