{"id":8378,"date":"2025-01-02T06:00:12","date_gmt":"2025-01-02T03:00:12","guid":{"rendered":"https:\/\/fatihsoysal.com\/blog\/streamlit-ile-temel-veri-gorsellestirme-uygulamasi\/"},"modified":"2025-01-02T06:00:12","modified_gmt":"2025-01-02T03:00:12","slug":"streamlit-ile-temel-veri-gorsellestirme-uygulamasi","status":"publish","type":"post","link":"https:\/\/fatihsoysal.com\/blog\/streamlit-ile-temel-veri-gorsellestirme-uygulamasi\/","title":{"rendered":"Streamlit ile Temel Veri G\u00f6rselle\u015ftirme Uygulamas\u0131"},"content":{"rendered":"

<\/p>\n

Streamlit ile Temel Veri G\u00f6rselle\u015ftirme Uygulamas\u0131<\/p>\n

Merhaba! Ben Fatih Soysal ve bu yaz\u0131da, Python programlama dili ve Streamlit k\u00fct\u00fcphanesini kullanarak basit bir veri g\u00f6rselle\u015ftirme web uygulamas\u0131 olu\u015fturmay\u0131 ad\u0131m ad\u0131m a\u00e7\u0131klayaca\u011f\u0131m. Bu uygulama, verilerinizi g\u00f6rsel olarak analiz etmenizi ve sonu\u00e7lar\u0131 kolayca payla\u015fman\u0131z\u0131 sa\u011flar. \u00d6ncelikle Streamlit’i kurman\u0131z gerekiyor. Bunun i\u00e7in terminal veya komut sat\u0131r\u0131n\u0131za pip install streamlit<\/code> komutunu yazman\u0131z yeterlidir.<\/p>\n

Gerekli K\u00fct\u00fcphanelerin \u0130\u00e7e Aktar\u0131m\u0131<\/h2>\n

Ba\u015flamadan \u00f6nce, projemizde kullanaca\u011f\u0131m\u0131z k\u00fct\u00fcphaneleri i\u00e7e aktaral\u0131m. Bu \u00f6rnekte, veri manip\u00fclasyonu i\u00e7in Pandas, g\u00f6rselle\u015ftirme i\u00e7in Matplotlib ve uygulaman\u0131n temelini olu\u015fturacak Streamlit’i kullanaca\u011f\u0131z. A\u015fa\u011f\u0131daki kod blo\u011fu, bu k\u00fct\u00fcphaneleri i\u00e7e aktarman\u0131n nas\u0131l yap\u0131ld\u0131\u011f\u0131n\u0131 g\u00f6stermektedir:<\/p>\n

\nimport streamlit as st\nimport pandas as pd\nimport matplotlib.pyplot as plt\n<\/code><\/pre>\n
Veri Y\u00fcklenmesi ve \u0130\u015flenmesi<\/h2>\n
\u015eimdi, g\u00f6rselle\u015ftirece\u011fimiz veri k\u00fcmesini y\u00fckleyip i\u015fleyelim. Bu \u00f6rnekte, basit bir CSV dosyas\u0131 kullanaca\u011f\u0131z.  Ancak, siz farkl\u0131 veri kaynaklar\u0131ndan da veri y\u00fckleyebilirsiniz.  Pandas k\u00fct\u00fcphanesi, CSV dosyalar\u0131n\u0131 okumak i\u00e7in olduk\u00e7a kullan\u0131\u015fl\u0131d\u0131r.  \u00d6rne\u011fin,  pd.read_csv(\"veriler.csv\")<\/code> komutu verilerinizi y\u00fckler.  Ard\u0131ndan, verilerinizi incelemek ve istedi\u011finiz gibi i\u015flemek i\u00e7in Pandas fonksiyonlar\u0131n\u0131 kullanabilirsiniz.  \u00d6rne\u011fin, veri k\u00fcmesinin ilk birka\u00e7 sat\u0131r\u0131n\u0131 g\u00f6r\u00fcnt\u00fclemek i\u00e7in df.head()<\/code> fonksiyonunu kullanabilirsiniz.<\/p>\n
Veri G\u00f6rselle\u015ftirmesi ve Streamlit Uygulamas\u0131<\/h2>\n
Verilerimizi i\u015fledikten sonra, s\u0131ra geldi g\u00f6rselle\u015ftirmeye. Matplotlib k\u00fct\u00fcphanesini kullanarak \u00e7e\u015fitli grafikler olu\u015fturabiliriz.  Streamlit, bu grafikleri web uygulamam\u0131za kolayca entegre etmemizi sa\u011flar.  A\u015fa\u011f\u0131daki kod par\u00e7as\u0131, bir \u00e7ubuk grafi\u011fi olu\u015fturup Streamlit ile g\u00f6r\u00fcnt\u00fclemenin nas\u0131l yap\u0131ld\u0131\u011f\u0131n\u0131 g\u00f6stermektedir:<\/p>\n
\nst.title(\"Veri G\u00f6rselle\u015ftirme Uygulamas\u0131\")\nst.write(\"Bu uygulama, verilerinizi g\u00f6rsel olarak analiz etmenizi sa\u011flar.\")\n\n#Veri Y\u00fckleme (veriler.csv dosyas\u0131 olmas\u0131 gerekmektedir)\ndf = pd.read_csv(\"veriler.csv\")\n\n# \u00c7ubuk Grafi\u011fi\nfig, ax = plt.subplots()\nax.bar(df[\"kategori\"], df[\"de\u011fer\"])\nst.pyplot(fig) \n<\/code><\/pre>\n
Bu kod, \u00f6ncelikle uygulaman\u0131n ba\u015fl\u0131\u011f\u0131n\u0131 ve k\u0131sa bir a\u00e7\u0131klamas\u0131n\u0131 yazar. Sonras\u0131nda verileri y\u00fckleyip, matplotlib ile \u00e7ubuk grafi\u011fini olu\u015fturur ve streamlit.pyplot ile uygulamada g\u00f6r\u00fcnt\u00fcler.  Daha karma\u015f\u0131k grafikler ve interaktif \u00f6zellikler i\u00e7in Seaborn k\u00fct\u00fcphanesini de kullanabilirsiniz.  Streamlit’in sundu\u011fu di\u011fer bile\u015fenleri (\u00f6rne\u011fin, slider, se\u00e7ici vb.) kullanarak uygulaman\u0131z\u0131 daha etkile\u015fimli hale getirebilirsiniz.  Daha detayl\u0131 bilgi i\u00e7in Streamlit dok\u00fcmanlar\u0131na<\/a> g\u00f6z atabilirsiniz.<\/p>\n
Uygulamay\u0131 \u00c7al\u0131\u015ft\u0131rma<\/h2>\n
T\u00fcm kodlar\u0131 yazd\u0131ktan sonra, terminal veya komut sat\u0131r\u0131nda streamlit run uygulamam.py<\/code> komutunu \u00e7al\u0131\u015ft\u0131rarak uygulaman\u0131z\u0131 ba\u015flatabilirsiniz (uygulamam.py dosya ad\u0131n\u0131z).  Bu komut, uygulaman\u0131z\u0131 yerel bir web sunucusunda \u00e7al\u0131\u015ft\u0131racakt\u0131r ve uygulaman\u0131za taray\u0131c\u0131n\u0131zdan eri\u015febilirsiniz.  Uygulamay\u0131 kapatmak i\u00e7in terminaldeki sunucuyu durdurman\u0131z yeterli olacakt\u0131r.<\/p>\n
Umar\u0131m bu basit \u00f6rnek size Streamlit ile veri g\u00f6rselle\u015ftirme uygulamas\u0131 geli\u015ftirme konusunda yard\u0131mc\u0131 olmu\u015ftur.  Daha geli\u015fmi\u015f uygulamalar i\u00e7in Streamlit’in sundu\u011fu di\u011fer \u00f6zelliklerini ke\u015ffetmenizi \u00f6neririm.  Kendi web sitemde, Python ve veri bilimiyle ilgili daha fazla i\u00e7erik bulabilirsiniz: https:\/\/fatihsoysal.com<\/a><\/p>\n
#Etiketler
\nStreamlit, Python, Veri G\u00f6rselle\u015ftirme, Web Uygulamas\u0131, Veri Analizi, Matplotlib, Seaborn, Pandas, CSV, Data Visualization, Web App, Data Analysis<\/p>\n
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