{"id":22512,"date":"2025-05-29T14:30:15","date_gmt":"2025-05-29T11:30:15","guid":{"rendered":"https:\/\/fatihsoysal.com\/blog\/pandas-olmadan-buyuk-veri-donusumleri-en-iyi-cozumler\/"},"modified":"2025-05-29T14:30:15","modified_gmt":"2025-05-29T11:30:15","slug":"pandas-olmadan-buyuk-veri-donusumleri-en-iyi-cozumler","status":"publish","type":"post","link":"https:\/\/fatihsoysal.com\/blog\/pandas-olmadan-buyuk-veri-donusumleri-en-iyi-cozumler\/","title":{"rendered":"Pandas Olmadan B\u00fcy\u00fck Veri D\u00f6n\u00fc\u015f\u00fcmleri: En \u0130yi \u00c7\u00f6z\u00fcmler"},"content":{"rendered":"<p><body><\/p>\n<p>Pandas Olmadan B\u00fcy\u00fck Veri D\u00f6n\u00fc\u015f\u00fcmleri: En \u0130yi \u00c7\u00f6z\u00fcmler<\/p>\n<p>Pandas, veri bilimi d\u00fcnyas\u0131nda pop\u00fcler bir ara\u00e7 olsa da, b\u00fcy\u00fck veri k\u00fcmeleriyle \u00e7al\u0131\u015f\u0131rken performans sorunlar\u0131na yol a\u00e7abilir.  Bu makalede, Pandas&#8217;\u0131n s\u0131n\u0131rlamalar\u0131n\u0131 a\u015fman\u0131n ve b\u00fcy\u00fck veri d\u00f6n\u00fc\u015f\u00fcmlerini verimli bir \u015fekilde y\u00f6netmenin yollar\u0131n\u0131 inceleyece\u011fiz.  \u00d6ncelikle, mevcut durum de\u011ferlendirmesi yapmak \u00f6nemlidir.  Veri setiniz ne kadar b\u00fcy\u00fck?  Hangi d\u00f6n\u00fc\u015f\u00fcmleri uygulaman\u0131z gerekiyor?  Bu sorular\u0131n cevaplar\u0131, en uygun \u00e7\u00f6z\u00fcm\u00fc belirlemenize yard\u0131mc\u0131 olacakt\u0131r. <\/p>\n<h2>Pandas&#8217;\u0131n S\u0131n\u0131rlamalar\u0131 ve Alternatifleri<\/h2>\n<p>Pandas, t\u00fcm veriyi belle\u011fe y\u00fckledi\u011fi i\u00e7in b\u00fcy\u00fck veri setleriyle m\u00fccadele eder.  Bu, bellek yetersizli\u011fi hatalar\u0131na ve yava\u015f performansa yol a\u00e7abilir.  Neyse ki, Pandas&#8217;\u0131n yerini alabilecek g\u00fc\u00e7l\u00fc alternatifler mevcuttur.  \u0130\u015fte en pop\u00fcler se\u00e7eneklerden baz\u0131lar\u0131:<\/p>\n<h3>Dask: Paralel \u0130\u015fleme G\u00fcc\u00fc<\/h3>\n<p>Dask, Pandas&#8217;a benzer bir API sunarak ge\u00e7i\u015fi kolayla\u015ft\u0131r\u0131r.  Ancak, verileri par\u00e7alara b\u00f6lerek ve bunlar\u0131 paralel olarak i\u015fleyerek Pandas&#8217;\u0131n dezavantajlar\u0131n\u0131 ortadan kald\u0131r\u0131r. B\u00fcy\u00fck veri k\u00fcmeleri i\u00e7in m\u00fckemmel bir performans sunar.  \u00d6rne\u011fin, Dask DataFrame&#8217;leri kullanarak b\u00fcy\u00fck bir CSV dosyas\u0131n\u0131 okuyup i\u015flemek olduk\u00e7a basittir:<\/p>\n<pre><code>\nimport dask.dataframe as dd\n\n# B\u00fcy\u00fck CSV dosyas\u0131n\u0131 okuyun\ndf = dd.read_csv(\"big_data.csv\")\n\n# D\u00f6n\u00fc\u015f\u00fcmleri uygulay\u0131n (\u00f6rne\u011fin, bir s\u00fctunu yeniden adland\u0131r\u0131n)\ndf = df.rename(columns={\"old_column\": \"new_column\"})\n\n# Sonu\u00e7lar\u0131 kaydedin\ndf.to_csv(\"transformed_data.csv\")\n<\/code><\/pre>\n<h3>Vaex: Bellek Verimlili\u011fi<\/h3>\n<p>Vaex, \u00e7ok b\u00fcy\u00fck veri k\u00fcmelerini do\u011frudan diskten i\u015flemek i\u00e7in tasarlanm\u0131\u015ft\u0131r.  Verileri belle\u011fe y\u00fcklemek yerine, Vaex lazy evaluation kullan\u0131r.  Yani, ancak gerekti\u011finde veriler okunur ve i\u015flenir.  Bu sayede bellek t\u00fcketimi minimuma indirilir.  Vaex, \u00f6zellikle say\u0131sal ve kategorik verilerle \u00e7al\u0131\u015fanlar i\u00e7in idealdir.  \u00d6zellikle veri g\u00f6rselle\u015ftirme konusunda olduk\u00e7a ba\u015far\u0131l\u0131d\u0131r.<\/p>\n<h3>Modin: Pandas&#8217;\u0131n Paralel Versiyonu<\/h3>\n<p>Modin, Pandas API&#8217;sini koruyarak paralel i\u015fleme yetenekleri kazand\u0131r\u0131r.  Pandas kodunuzu minimal de\u011fi\u015fiklikle Modin&#8217;e ta\u015f\u0131yabilirsiniz.  Bu, Pandas&#8217;a a\u015fina olanlar i\u00e7in ge\u00e7i\u015fi kolayla\u015ft\u0131r\u0131r.  Ancak, Modin&#8217;in performans\u0131 verinin yap\u0131s\u0131na ve kullan\u0131lan d\u00f6n\u00fc\u015f\u00fcmlere ba\u011fl\u0131 olarak de\u011fi\u015febilir.  Performans \u00f6l\u00e7\u00fcm\u00fc her zaman i\u00e7in \u00f6nemlidir.<\/p>\n<h2>En Sevdi\u011fim \u00c7\u00f6z\u00fcm Y\u00f6ntemleri ve \u0130pu\u00e7lar\u0131<\/h2>\n<p>B\u00fcy\u00fck veri d\u00f6n\u00fc\u015f\u00fcmlerinde ba\u015far\u0131l\u0131 olman\u0131n anahtar\u0131, do\u011fru arac\u0131 se\u00e7mek ve verimli kodlama tekniklerini kullanmakt\u0131r.  \u0130\u015fte birka\u00e7 ipucu:<\/p>\n<ul>\n<li>Veri setinizi iyice inceleyin ve d\u00f6n\u00fc\u015f\u00fcm gereksinimlerinizi belirleyin.<\/li>\n<li>Herhangi bir d\u00f6n\u00fc\u015f\u00fcm i\u015flemi yapmadan \u00f6nce verilerinizi temizlemeyi unutmay\u0131n.  Bu size daha g\u00fcvenilir sonu\u00e7lar sunacakt\u0131r.<\/li>\n<li>Paralel i\u015fleme kullan\u0131n.  Bu, i\u015flem s\u00fcrelerini \u00f6nemli \u00f6l\u00e7\u00fcde azaltman\u0131za yard\u0131mc\u0131 olacakt\u0131r.<\/li>\n<li>D\u00f6n\u00fc\u015f\u00fcmleri m\u00fcmk\u00fcn oldu\u011funca k\u00fc\u00e7\u00fck par\u00e7alara b\u00f6l\u00fcn ve her par\u00e7ay\u0131 ayr\u0131 ayr\u0131 i\u015fleyin. B\u00f6ylelikle hata ay\u0131klama daha kolay olur.<\/li>\n<li>\u0130\u015flem sonunda her zaman veri kalitesini kontrol edin.  Herhangi bir beklenmedik durum olup olmad\u0131\u011f\u0131n\u0131 teyit edin.<\/li>\n<\/ul>\n<p>B\u00fcy\u00fck veri d\u00f6n\u00fc\u015f\u00fcmleri zorlu olabilir, ancak do\u011fru ara\u00e7lar ve tekniklerle bu zorluklar\u0131n \u00fcstesinden gelebilirsiniz.  Dask, Vaex ve Modin gibi ara\u00e7lar, Pandas&#8217;\u0131n s\u0131n\u0131rlamalar\u0131n\u0131 a\u015fmak ve b\u00fcy\u00fck veri setlerini verimli bir \u015fekilde d\u00f6n\u00fc\u015ft\u00fcrmek i\u00e7in g\u00fc\u00e7l\u00fc se\u00e7enekler sunar.  Unutmay\u0131n ki, en iyi \u00e7\u00f6z\u00fcm her zaman projenizin \u00f6zel gereksinimlerine ba\u011fl\u0131d\u0131r.  Dolay\u0131s\u0131yla, farkl\u0131 se\u00e7enekleri deneyerek en uygun olan\u0131 bulman\u0131z \u00f6nemlidir. <\/p>\n<p>Daha fazla veri bilimi ipucu ve teknikleri i\u00e7in <a href=\"https:\/\/fatihsoysal.com\">fatihsoysal.com<\/a> adresini ziyaret edebilirsiniz.<\/p>\n<h3>#Etiketler<\/h3>\n<p>#B\u00fcy\u00fckVeri #VeriD\u00f6n\u00fc\u015f\u00fcm\u00fc #Pandas #Dask #Vaex #Modin #Python #VeriBilimi #Veri\u0130\u015fleme #BellekVerimlili\u011fi #Paralel\u0130\u015fleme<br \/>\n<\/body><br \/>\n<\/html><\/p>\n","protected":false},"excerpt":{"rendered":"Pandas Olmadan B\u00fcy\u00fck Veri D\u00f6n\u00fc\u015f\u00fcmleri: En \u0130yi \u00c7\u00f6z\u00fcmler Pandas, veri bilimi d\u00fcnyas\u0131nda pop\u00fcler bir ara\u00e7 olsa da, b\u00fcy\u00fck&hellip;","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":[1],"tags":[],"class_list":{"0":"post-22512","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-genel","7":"cs-entry","8":"cs-video-wrap"},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.5 (Yoast SEO v25.3.1) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Pandas Olmadan B\u00fcy\u00fck Veri D\u00f6n\u00fc\u015f\u00fcmleri: En \u0130yi \u00c7\u00f6z\u00fcmler<\/title>\n<meta name=\"description\" content=\"Pandas, veri bilimi d\u00fcnyas\u0131nda pop\u00fcler bir ara\u00e7 olsa da, b\u00fcy\u00fck veri k\u00fcmeleriyle \u00e7al\u0131\u015f\u0131rken performans sorunlar\u0131na yol a\u00e7abilir. Bu makalede, Pandas&#039;\u0131n s\u0131n\u0131rlamalar\u0131n\u0131 a\u015fman\u0131n ve b\u00fcy\u00fck veri d\u00f6n\u00fc\u015f\u00fcmlerini verimli bir \u015fekilde y\u00f6netmenin yollar\u0131n\u0131 inceleyece\u011fiz. \u00d6ncelikle, mevcut durum de\u011ferlendirmesi yapmak \u00f6nemlidir. Veri setiniz ne kadar b\u00fcy\u00fck? Hangi d\u00f6n\u00fc\u015f\u00fcmleri uygulaman\u0131z gerekiyor? Bu sorular\u0131n cevaplar\u0131, en uygun \u00e7\u00f6z\u00fcm\u00fc belirlemenize yard\u0131mc\u0131 olacakt\u0131r.\" \/>\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\/pandas-olmadan-buyuk-veri-donusumleri-en-iyi-cozumler\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas Olmadan B\u00fcy\u00fck Veri D\u00f6n\u00fc\u015f\u00fcmleri: En \u0130yi \u00c7\u00f6z\u00fcmler\" \/>\n<meta property=\"og:description\" content=\"Pandas, veri bilimi d\u00fcnyas\u0131nda pop\u00fcler bir ara\u00e7 olsa da, b\u00fcy\u00fck veri k\u00fcmeleriyle \u00e7al\u0131\u015f\u0131rken performans sorunlar\u0131na yol a\u00e7abilir. Bu makalede, Pandas&#039;\u0131n s\u0131n\u0131rlamalar\u0131n\u0131 a\u015fman\u0131n ve b\u00fcy\u00fck veri d\u00f6n\u00fc\u015f\u00fcmlerini verimli bir \u015fekilde y\u00f6netmenin yollar\u0131n\u0131 inceleyece\u011fiz. \u00d6ncelikle, mevcut durum de\u011ferlendirmesi yapmak \u00f6nemlidir. Veri setiniz ne kadar b\u00fcy\u00fck? Hangi d\u00f6n\u00fc\u015f\u00fcmleri uygulaman\u0131z gerekiyor? Bu sorular\u0131n cevaplar\u0131, en uygun \u00e7\u00f6z\u00fcm\u00fc belirlemenize yard\u0131mc\u0131 olacakt\u0131r.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/fatihsoysal.com\/blog\/pandas-olmadan-buyuk-veri-donusumleri-en-iyi-cozumler\/\" \/>\n<meta property=\"og:site_name\" content=\"Kodlar\u0131n Gizemli D\u00fcnyas\u0131\" \/>\n<meta property=\"article:published_time\" content=\"2025-05-29T11:30:15+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=\"3 dakika\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/pandas-olmadan-buyuk-veri-donusumleri-en-iyi-cozumler\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/pandas-olmadan-buyuk-veri-donusumleri-en-iyi-cozumler\/\"},\"author\":{\"name\":\"Fatih Soysal\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"headline\":\"Pandas Olmadan B\u00fcy\u00fck Veri D\u00f6n\u00fc\u015f\u00fcmleri: En \u0130yi \u00c7\u00f6z\u00fcmler\",\"datePublished\":\"2025-05-29T11:30:15+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/pandas-olmadan-buyuk-veri-donusumleri-en-iyi-cozumler\/\"},\"wordCount\":633,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/fatihsoysal.com\/blog\/pandas-olmadan-buyuk-veri-donusumleri-en-iyi-cozumler\/#respond\"]}],\"copyrightYear\":\"2025\",\"copyrightHolder\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#organization\"}},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/pandas-olmadan-buyuk-veri-donusumleri-en-iyi-cozumler\/\",\"url\":\"https:\/\/fatihsoysal.com\/blog\/pandas-olmadan-buyuk-veri-donusumleri-en-iyi-cozumler\/\",\"name\":\"Pandas Olmadan B\u00fcy\u00fck Veri D\u00f6n\u00fc\u015f\u00fcmleri: En \u0130yi \u00c7\u00f6z\u00fcmler\",\"isPartOf\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#website\"},\"datePublished\":\"2025-05-29T11:30:15+00:00\",\"description\":\"Pandas, veri bilimi d\u00fcnyas\u0131nda pop\u00fcler bir ara\u00e7 olsa da, b\u00fcy\u00fck veri k\u00fcmeleriyle \u00e7al\u0131\u015f\u0131rken performans sorunlar\u0131na yol a\u00e7abilir. 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