{"id":25512,"date":"2025-07-07T15:15:23","date_gmt":"2025-07-07T12:15:23","guid":{"rendered":"https:\/\/fatihsoysal.com\/blog\/postgresql-ortalama-medyan-ve-mod-hesaplama\/"},"modified":"2025-07-07T15:15:23","modified_gmt":"2025-07-07T12:15:23","slug":"postgresql-ortalama-medyan-ve-mod-hesaplama","status":"publish","type":"post","link":"https:\/\/fatihsoysal.com\/blog\/postgresql-ortalama-medyan-ve-mod-hesaplama\/","title":{"rendered":"PostgreSQL: Ortalama, Medyan ve Mod Hesaplama"},"content":{"rendered":"

# PostgreSQL’de Ortalama, Medyan ve Mod Hesaplama<\/p>\n

PostgreSQL veritaban\u0131n\u0131zda sakl\u0131 olan verilerden anlaml\u0131 sonu\u00e7lar \u00e7\u0131karmak i\u00e7in istatistiksel analizler yapmak \u015fartt\u0131r. Bu analizlerin en temel unsurlar\u0131 ortalama (mean), medyan (median) ve mod (mode) hesaplamalar\u0131d\u0131r. Bu makalede, PostgreSQL kullanarak bu \u00fc\u00e7 istatisti\u011fi nas\u0131l hesaplayaca\u011f\u0131n\u0131z\u0131, performans\u0131 nas\u0131l optimize edece\u011finizi ve kar\u015f\u0131la\u015fabilece\u011finiz zorluklar\u0131 nas\u0131l a\u015faca\u011f\u0131n\u0131z\u0131 ad\u0131m ad\u0131m \u00f6\u011freneceksiniz. Veri analizi d\u00fcnyas\u0131na ad\u0131m atmak ve PostgreSQL becerilerinizi geli\u015ftirmek i\u00e7in ideal bir rehberdir.<\/p>\n

\u00d6\u011frenme Yol Haritas\u0131<\/strong><\/p>\n

Bu makale, PostgreSQL’de ortalama, medyan ve mod hesaplamas\u0131n\u0131 \u00fc\u00e7 seviyede ele almaktad\u0131r:<\/p>\n

Yeni Ba\u015flayan:<\/strong> Temel SQL fonksiyonlar\u0131 ile ortalama, medyan ve mod hesaplama. Basit \u00f6rnekler ve ad\u0131m ad\u0131m a\u00e7\u0131klamalar.<\/p>\n

Orta:<\/strong> Ger\u00e7ek d\u00fcnya senaryolar\u0131, daha karma\u015f\u0131k sorgular ve performans optimizasyon teknikleri.<\/p>\n

\u0130leri D\u00fczey:<\/strong> Karma\u015f\u0131k veri k\u00fcmeleri, performans analizi, s\u0131n\u0131r durumlar\u0131 (edge cases) ve ileri d\u00fczey optimizasyon stratejileri.<\/p>\n

PostgreSQL’de Ortalama (Mean) Hesaplama: Nas\u0131l Yap\u0131l\u0131r?<\/strong><\/p>\n

Ortalama, bir veri k\u00fcmesindeki t\u00fcm de\u011ferlerin toplam\u0131n\u0131n de\u011fer say\u0131s\u0131na b\u00f6l\u00fcnmesiyle bulunur. PostgreSQL’de AVG()<\/code> fonksiyonu ile kolayca hesaplan\u0131r.<\/p>\n

Yeni Ba\u015flayan:<\/strong><\/p>\n

\u00d6rne\u011fin, bir urunler<\/code> tablosunda her \u00fcr\u00fcn\u00fcn fiyat\u0131n\u0131n ortalamas\u0131n\u0131 bulmak i\u00e7in \u015fu sorguyu kullanabiliriz:<\/p>\n

SELECT AVG(fiyat) AS ortalama_fiyat\nFROM urunler;<\/code><\/pre>\n
Bu sorgu, urunler<\/code> tablosundaki t\u00fcm \u00fcr\u00fcnlerin fiyatlar\u0131n\u0131n ortalamas\u0131n\u0131 hesaplar ve sonucu ortalama_fiyat<\/code> olarak adland\u0131r\u0131r.<\/p>\n
Orta:<\/strong><\/p>\n
\u015eimdi,  \u00fcr\u00fcn kategorilerine g\u00f6re ortalama fiyatlar\u0131 hesaplayal\u0131m:<\/p>\n
SELECT kategori, AVG(fiyat) AS ortalama_fiyat\nFROM urunler\nGROUP BY kategori;<\/code><\/pre>\n
Bu sorgu, her kategori i\u00e7in ayr\u0131 ayr\u0131 ortalama fiyat\u0131 hesaplar.  GROUP BY<\/code> kullan\u0131m\u0131, verileri kategorilere g\u00f6re grupland\u0131rmam\u0131z\u0131 sa\u011flar.  Daha b\u00fcy\u00fck veri k\u00fcmeleri i\u00e7in performans\u0131 art\u0131rmak i\u00e7in uygun indeksler olu\u015fturman\u0131z \u00f6nemlidir.  [Fatih Soysal’\u0131n PostgreSQL performans optimizasyonu hakk\u0131ndaki yaz\u0131lar\u0131n\u0131](https:\/\/fatihsoysal.com) inceleyerek daha fazla bilgi edinebilirsiniz.<\/p>\n
\u0130leri D\u00fczey:<\/strong><\/p>\n
\u00c7ok b\u00fcy\u00fck veri k\u00fcmeleri i\u00e7in, AVG()<\/code> fonksiyonu performans sorunlar\u0131na yol a\u00e7abilir. Bu durumlarda,  par\u00e7al\u0131 (partitioned) tablolar veya materyalize g\u00f6r\u00fcn\u00fcmler (materialized views) kullanarak performans\u0131 art\u0131rabilirsiniz.  Ayr\u0131ca,  EXPLAIN ANALYZE<\/code> komutuyla sorgu plan\u0131n\u0131 inceleyerek darbo\u011fazlar\u0131 tespit edebilir ve optimizasyon yapabilirsiniz.  \u00d6rne\u011fin,  b\u00fcy\u00fck bir veri k\u00fcmesinde  WHERE<\/code> ko\u015fulu kullanarak filtreleme yapmak performans\u0131 \u00f6nemli \u00f6l\u00e7\u00fcde iyile\u015ftirebilir.<\/p>\n
PostgreSQL’de Medyan (Median) Hesaplama: Nas\u0131l Yap\u0131l\u0131r?<\/strong><\/p>\n
Medyan, s\u0131ralanm\u0131\u015f bir veri k\u00fcmesinin tam ortas\u0131ndaki de\u011ferdir.  PostgreSQL’de medyan\u0131 do\u011frudan hesaplayan bir fonksiyon bulunmamaktad\u0131r. Ancak,  PERCENTILE_CONT()<\/code> fonksiyonu ile hesaplayabiliriz.<\/p>\n
Yeni Ba\u015flayan:<\/strong><\/p>\n
urunler<\/code> tablosundaki fiyatlar\u0131n medyan\u0131n\u0131 bulmak i\u00e7in:<\/p>\n
SELECT PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY fiyat) AS medyan_fiyat\nFROM urunler;<\/code><\/pre>\n
Bu sorgu, fiyat s\u00fctununu s\u0131ralar ve %50’lik percentili (yani medyan\u0131) hesaplar.<\/p>\n
Orta:<\/strong><\/p>\n
Medyan\u0131 kategori baz\u0131nda hesaplamak i\u00e7in:<\/p>\n
SELECT kategori, PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY fiyat) AS medyan_fiyat\nFROM urunler\nGROUP BY kategori;<\/code><\/pre>\n
Bu, her kategori i\u00e7in ayr\u0131 ayr\u0131 medyan fiyat\u0131 hesaplar.  B\u00fcy\u00fck veri k\u00fcmeleri i\u00e7in  PERCENTILE_CONT()<\/code>  fonksiyonu yava\u015f olabilir. Bu durumda,  \u00f6rnekleme (sampling) teknikleri kullanarak daha h\u0131zl\u0131 bir yakla\u015f\u0131m elde edebilirsiniz.<\/p>\n
\u0130leri D\u00fczey:<\/strong><\/p>\n
PERCENTILE_CONT()<\/code> fonksiyonu,  NULL de\u011ferleri dikkate almaz.  NULL de\u011ferleri nas\u0131l ele alaca\u011f\u0131n\u0131z\u0131 belirlemek \u00f6nemlidir.  \u00d6rne\u011fin,  NULL de\u011ferleri s\u0131f\u0131r olarak ele almak isterseniz,  COALESCE()<\/code> fonksiyonunu kullanabilirsiniz.  Ayr\u0131ca,  \u00e7ok b\u00fcy\u00fck veri k\u00fcmeleri i\u00e7in  APPROXIMATE QUERY PROCESSING (AQP) tekniklerini kullanarak medyan\u0131 yakla\u015f\u0131k olarak hesaplayabilirsiniz.  Bu teknikler,  kesin sonu\u00e7 yerine h\u0131zl\u0131 bir yakla\u015f\u0131m sa\u011flar.<\/p>\n
PostgreSQL’de Mod (Mode) Hesaplama: Nas\u0131l Yap\u0131l\u0131r?<\/strong><\/p>\n
Mod, bir veri k\u00fcmesinde en s\u0131k tekrar eden de\u011ferdir. PostgreSQL’de mod i\u00e7in yerle\u015fik bir fonksiyon bulunmaz.  Ancak,  SQL sorgular\u0131 kullanarak hesaplayabiliriz.<\/p>\n
Yeni Ba\u015flayan:<\/strong><\/p>\n
Basit bir y\u00f6ntem,  GROUP BY<\/code> ve COUNT()<\/code> fonksiyonlar\u0131n\u0131 kullanarak her de\u011ferin tekrar say\u0131s\u0131n\u0131 bulmak ve en y\u00fcksek say\u0131ya sahip de\u011feri se\u00e7mektir.  Bu y\u00f6ntem,  \u00e7ok say\u0131da farkl\u0131 de\u011fer i\u00e7in performans sorunlar\u0131na yol a\u00e7abilir.<\/p>\n
WITH frekanslar AS (\n    SELECT fiyat, COUNT(*) AS sayi\n    FROM urunler\n    GROUP BY fiyat\n),\nmax_frekans AS (\n    SELECT MAX(sayi) AS max_sayi\n    FROM frekanslar\n)\nSELECT fiyat AS mod_fiyat\nFROM frekanslar\nWHERE sayi = (SELECT max_sayi FROM max_frekans);<\/code><\/pre>\n
Bu sorgu, \u00f6nce her fiyat\u0131n tekrar say\u0131s\u0131n\u0131 hesaplar, daha sonra en y\u00fcksek tekrar say\u0131s\u0131n\u0131 bulur ve son olarak bu say\u0131ya sahip fiyat\u0131 mod olarak se\u00e7er.<\/p>\n
Orta:<\/strong><\/p>\n
Bu y\u00f6ntem,  birden fazla mod varsa sadece bir tanesini d\u00f6nd\u00fcr\u00fcr.  T\u00fcm modlar\u0131 bulmak i\u00e7in daha karma\u015f\u0131k bir sorgu gereklidir.  Ayr\u0131ca,  b\u00fcy\u00fck veri k\u00fcmeleri i\u00e7in performans\u0131 art\u0131rmak i\u00e7in indeksleme ve optimizasyon teknikleri kullan\u0131lmal\u0131d\u0131r.<\/p>\n
\u0130leri D\u00fczey:<\/strong><\/p>\n
\u00c7ok b\u00fcy\u00fck veri k\u00fcmeleri veya y\u00fcksek kardinaliteli (\u00e7ok say\u0131da farkl\u0131 de\u011fer) s\u00fctunlar i\u00e7in,  modu yakla\u015f\u0131k olarak hesaplamak daha verimli olabilir.  \u00d6rne\u011fin,  veri k\u00fcmesini \u00f6rnekleyerek (sampling) veya histogram kullanarak yakla\u015f\u0131k bir mod hesaplayabilirsiniz.  Bu teknikler,  kesin sonu\u00e7 yerine h\u0131zl\u0131 bir yakla\u015f\u0131m sa\u011flar.<\/p>\n
Ger\u00e7ek D\u00fcnya Senaryolar\u0131 ve Vaka Analizleri<\/strong><\/p>\n
Senaryo 1: E-ticaret Sitesi:<\/strong>  Bir e-ticaret sitesinin \u00fcr\u00fcn sat\u0131\u015f verilerinde,  en \u00e7ok sat\u0131lan \u00fcr\u00fcn\u00fcn fiyat\u0131n\u0131n medyan\u0131n\u0131 bulmak isteyebilirsiniz.  Bu,  \u00fcr\u00fcn fiyatland\u0131rmas\u0131 stratejileri i\u00e7in faydal\u0131 bir bilgi olabilir.<\/p>\n
Senaryo 2: Sa\u011fl\u0131k Sekt\u00f6r\u00fc:<\/strong>  Hastane kay\u0131tlar\u0131nda,  hasta ya\u015flar\u0131n\u0131n ortalamas\u0131n\u0131, medyan\u0131n\u0131 ve modunu hesaplayarak hasta demografisini analiz edebilirsiniz.<\/p>\n
Senaryo 3: Finans:<\/strong>  Bir finans kurulu\u015funun m\u00fc\u015fteri hesap bakiyelerinin ortalamas\u0131n\u0131 ve medyan\u0131n\u0131 hesaplayarak m\u00fc\u015fteri portf\u00f6y\u00fcn\u00fcn da\u011f\u0131l\u0131m\u0131n\u0131 analiz edebilirsiniz.<\/p>\n
Performans Optimizasyonu<\/strong><\/p>\n
PostgreSQL’de istatistiksel hesaplamalar\u0131n performans\u0131n\u0131 art\u0131rmak i\u00e7in a\u015fa\u011f\u0131daki teknikleri kullanabilirsiniz:<\/p>\n
* Uygun \u0130ndeksler:<\/strong>  S\u0131k\u00e7a sorgulad\u0131\u011f\u0131n\u0131z s\u00fctunlara indeks olu\u015fturmak sorgu h\u0131z\u0131n\u0131 \u00f6nemli \u00f6l\u00e7\u00fcde art\u0131rabilir.
\n* Par\u00e7al\u0131 Tablolar:<\/strong>  B\u00fcy\u00fck tablolar\u0131 daha k\u00fc\u00e7\u00fck par\u00e7alara b\u00f6lmek,  sorgular\u0131 daha h\u0131zl\u0131 hale getirebilir.
\n* Materyalize G\u00f6r\u00fcn\u00fcmler:<\/strong>  S\u0131k kullan\u0131lan sorgular\u0131n sonu\u00e7lar\u0131n\u0131 \u00f6nceden hesaplay\u0131p saklamak,  sorgu s\u00fcresini k\u0131saltabilir.
\n* Sorgu Optimizasyonu:<\/strong>  EXPLAIN ANALYZE<\/code> komutuyla sorgu plan\u0131n\u0131 inceleyerek darbo\u011fazlar\u0131 tespit edebilir ve optimizasyon yapabilirsiniz.<\/p>\n
Sonu\u00e7<\/strong><\/p>\n
Bu makalede, PostgreSQL’de ortalama, medyan ve mod hesaplaman\u0131n temelinden ileri d\u00fczey tekniklerine kadar geni\u015f bir yelpazede bilgi sunduk.  Ger\u00e7ek d\u00fcnya \u00f6rnekleri ve performans optimizasyonu teknikleri ile konuyu daha iyi anlaman\u0131za yard\u0131mc\u0131 olmay\u0131 ama\u00e7lad\u0131k.  PostgreSQL’de istatistiksel analizler yaparak verilerinizden daha fazla de\u011fer elde edebilirsiniz.<\/p>\n
S\u0131k\u00e7a Sorulan Sorular:<\/strong><\/p>\n
1. PostgreSQL’de medyan\u0131 hesaplamak i\u00e7in ba\u015fka y\u00f6ntemler var m\u0131?<\/strong> Evet,  PERCENTILE_DISC()<\/code> fonksiyonu da kullan\u0131labilir, ancak  PERCENTILE_CONT()<\/code>  ile ayn\u0131 sonu\u00e7lar\u0131 vermez.<\/p>\n
2. \u00c7ok b\u00fcy\u00fck veri k\u00fcmeleri i\u00e7in hangi y\u00f6ntemleri \u00f6nerirsiniz?<\/strong> \u00c7ok b\u00fcy\u00fck veri k\u00fcmeleri i\u00e7in \u00f6rneklem alma (sampling),  yakla\u015f\u0131k sorgu i\u015fleme (AQP) teknikleri ve par\u00e7al\u0131 tablolar kullanman\u0131z\u0131 \u00f6neririz.<\/p>\n
3. NULL de\u011ferleri nas\u0131l ele almal\u0131y\u0131m?<\/strong>  COALESCE()<\/code> fonksiyonunu kullanarak NULL de\u011ferlerini istedi\u011finiz bir de\u011ferle de\u011fi\u015ftirebilirsiniz.<\/p>\n
4. Performans\u0131 nas\u0131l daha da iyile\u015ftirebilirim?<\/strong>  PostgreSQL ayarlar\u0131n\u0131 inceleyerek,  bellek kullan\u0131m\u0131 ve i\u015flemci kullan\u0131m\u0131n\u0131 optimize edebilirsiniz.<\/p>\n
5. \u0130leri d\u00fczey optimizasyon i\u00e7in hangi kaynaklar\u0131 \u00f6nerebilirsiniz?<\/strong>  PostgreSQL dok\u00fcmantasyonu ve Fatih Soysal’\u0131n blog yaz\u0131lar\u0131 ([https:\/\/fatihsoysal.com](https:\/\/fatihsoysal.com)) iyi bir ba\u015flang\u0131\u00e7 noktas\u0131 olabilir.<\/p>\n
Yazar: Fatih Soysal<\/p>\n","protected":false},"excerpt":{"rendered":"# PostgreSQL’de Ortalama, Medyan ve Mod Hesaplama PostgreSQL veritaban\u0131n\u0131zda sakl\u0131 olan verilerden anlaml\u0131 sonu\u00e7lar \u00e7\u0131karmak i\u00e7in istatistiksel analizler…","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"csco_page_header_type":"","csco_page_load_nextpost":"","csco_page_subscribe_form":"","csco_page_contact_form":"","footnotes":""},"categories":[644],"tags":[],"class_list":{"0":"post-25512","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-postgresql","7":"cs-entry","8":"cs-video-wrap"},"yoast_head":"\nPostgreSQL: Ortalama, Medyan ve Mod Hesaplama<\/title>\n<meta name=\"description\" content=\"Hi\u00e7bir etiketi bulunamad\u0131.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fatihsoysal.com\/blog\/postgresql-ortalama-medyan-ve-mod-hesaplama\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"PostgreSQL: Ortalama, Medyan ve Mod Hesaplama\" \/>\n<meta property=\"og:description\" content=\"Hi\u00e7bir etiketi bulunamad\u0131.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/fatihsoysal.com\/blog\/postgresql-ortalama-medyan-ve-mod-hesaplama\/\" \/>\n<meta property=\"og:site_name\" content=\"Kodlar\u0131n Gizemli D\u00fcnyas\u0131\" \/>\n<meta property=\"article:published_time\" content=\"2025-07-07T12:15:23+00:00\" \/>\n<meta name=\"author\" content=\"Fatih Soysal\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Yazan:\" \/>\n\t<meta name=\"twitter:data1\" content=\"Fatih Soysal\" \/>\n\t<meta name=\"twitter:label2\" content=\"Tahmini okuma s\u00fcresi\" \/>\n\t<meta name=\"twitter:data2\" content=\"6 dakika\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/postgresql-ortalama-medyan-ve-mod-hesaplama\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/postgresql-ortalama-medyan-ve-mod-hesaplama\/\"},\"author\":{\"name\":\"Fatih Soysal\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"headline\":\"PostgreSQL: Ortalama, Medyan ve Mod Hesaplama\",\"datePublished\":\"2025-07-07T12:15:23+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/postgresql-ortalama-medyan-ve-mod-hesaplama\/\"},\"wordCount\":1175,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"articleSection\":[\"PostgreSQL\"],\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/fatihsoysal.com\/blog\/postgresql-ortalama-medyan-ve-mod-hesaplama\/#respond\"]}],\"copyrightYear\":\"2025\",\"copyrightHolder\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#organization\"}},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/postgresql-ortalama-medyan-ve-mod-hesaplama\/\",\"url\":\"https:\/\/fatihsoysal.com\/blog\/postgresql-ortalama-medyan-ve-mod-hesaplama\/\",\"name\":\"PostgreSQL: Ortalama, Medyan ve Mod Hesaplama\",\"isPartOf\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#website\"},\"datePublished\":\"2025-07-07T12:15:23+00:00\",\"description\":\"Hi\u00e7bir etiketi bulunamad\u0131.\",\"breadcrumb\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/postgresql-ortalama-medyan-ve-mod-hesaplama\/#breadcrumb\"},\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/fatihsoysal.com\/blog\/postgresql-ortalama-medyan-ve-mod-hesaplama\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/postgresql-ortalama-medyan-ve-mod-hesaplama\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Anasayfa\",\"item\":\"https:\/\/fatihsoysal.com\/blog\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"PostgreSQL: Ortalama, Medyan ve Mod Hesaplama\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#website\",\"url\":\"https:\/\/fatihsoysal.com\/blog\/\",\"name\":\"Fatihsoysal.com\",\"description\":\"Blog - 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