Modern Veri G\u00f6rselle\u015ftirme Ara\u00e7lar\u0131: Streamlit, Dash ve Bokeh’e Kapsaml\u0131 Bir Bak\u0131\u015f<\/p>\n
Veri \u00e7a\u011f\u0131nda ya\u015f\u0131yoruz ve bu verinin anlam\u0131n\u0131 \u00e7\u0131karabilmek, i\u015f kararlar\u0131 almak i\u00e7in hayati \u00f6nem ta\u015f\u0131yor. Ancak, ham veriler genellikle anla\u015f\u0131lmas\u0131 zor ve karma\u015f\u0131k olabilir. \u0130\u015fte bu noktada, veri g\u00f6rselle\u015ftirme ara\u00e7lar\u0131 devreye giriyor. Streamlit, Dash ve Bokeh gibi modern ara\u00e7lar, karma\u015f\u0131k verileri etkileyici ve anla\u015f\u0131l\u0131r g\u00f6rsellerle sunarak, verilerden de\u011fer \u00e7\u0131karmay\u0131 kolayla\u015ft\u0131r\u0131yor. Bu makalede, bu \u00fc\u00e7 g\u00fc\u00e7l\u00fc arac\u0131 detayl\u0131 olarak inceleyece\u011fiz ve hangi senaryolar i\u00e7in en uygun oldu\u011funu belirleyece\u011fiz.<\/p>\n
Streamlit, Python tabanl\u0131 bir a\u00e7\u0131k kaynak veri g\u00f6rselle\u015ftirme k\u00fct\u00fcphanesidir. Di\u011fer k\u00fct\u00fcphanelere k\u0131yasla en b\u00fcy\u00fck avantaj\u0131, etkile\u015fimli veri uygulamalar\u0131n\u0131 inan\u0131lmaz bir h\u0131zla geli\u015ftirme olana\u011f\u0131 sunmas\u0131d\u0131r. Minimalist bir kodlama yakla\u015f\u0131m\u0131yla, birka\u00e7 sat\u0131r kodla etkile\u015fimli \u00e7izelgeler, haritalar ve di\u011fer g\u00f6rseller olu\u015fturabilirsiniz. Streamlit’in en \u00f6nemli \u00f6zelliklerinden biri de, kod de\u011fi\u015fikliklerini anl\u0131k olarak uygulamada g\u00f6rmenizi sa\u011flamas\u0131d\u0131r. Bu, h\u0131zl\u0131 prototipleme ve geli\u015ftirme i\u00e7in ideal bir ortam sa\u011flar.<\/p>\n
Streamlit’in temellerini anlamak i\u00e7in basit bir \u00f6rnek verelim:<\/p>\n
import streamlit as st\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\n# \u00d6rnek veri k\u00fcmesi\ndata = {'Kategori': ['A', 'B', 'C'], 'De\u011fer': [10, 20, 15]}\ndf = pd.DataFrame(data)\n\n# Streamlit uygulamas\u0131\nst.title(\"Streamlit \u00d6rne\u011fi\")\nst.write(\"Bu bir basit Streamlit uygulamas\u0131d\u0131r.\")\nst.dataframe(df)\n\n# Matplotlib ile \u00e7izelge olu\u015fturma\nplt.figure()\nplt.bar(df['Kategori'], df['De\u011fer'])\nplt.xlabel(\"Kategori\")\nplt.ylabel(\"De\u011fer\")\nst.pyplot(plt)<\/pre>\n<\/code><\/p>\n
Bu kod blo\u011fu, basit bir s\u00fctun grafi\u011fi i\u00e7eren bir Streamlit uygulamas\u0131 olu\u015fturur. st.title<\/code>, st.write<\/code> ve st.dataframe<\/code> gibi fonksiyonlar, i\u00e7eri\u011fi d\u00fczenlemek ve g\u00f6r\u00fcnt\u00fclemek i\u00e7in kullan\u0131l\u0131r. st.pyplot<\/code> fonksiyonu ise Matplotlib ile olu\u015fturulan grafikleri Streamlit uygulamas\u0131na entegre etmemizi sa\u011flar. Daha karma\u015f\u0131k uygulamalar i\u00e7in, Streamlit'in geni\u015f widget ve fonksiyon k\u00fct\u00fcphanesini kullanabilirsiniz. \u00d6rne\u011fin, kullan\u0131c\u0131 girdilerini almak i\u00e7in st.slider<\/code>, st.selectbox<\/code> gibi widget'lar kullan\u0131labilir.<\/p>\nStreamlit ayr\u0131ca, b\u00fcy\u00fck veri k\u00fcmelerini verimli bir \u015fekilde y\u00f6netmek i\u00e7in optimize edilmi\u015ftir. Y\u00fcksek performansl\u0131 uygulamalar geli\u015ftirmek i\u00e7in, verileri \u00f6nceden i\u015fleyip, Streamlit uygulamas\u0131nda sadece sonucu g\u00f6r\u00fcnt\u00fclemek \u00f6nemlidir.<\/p>\n
Streamlit ile Etkile\u015fimli Harita G\u00f6rselle\u015ftirmeleri Nas\u0131l Olu\u015fturulur?<\/h3>\n
Streamlit, Folium gibi k\u00fct\u00fcphanelerle entegre olarak etkile\u015fimli haritalar olu\u015fturman\u0131z\u0131 sa\u011flar. Bu sayede, co\u011frafi verileri g\u00f6rselle\u015ftirerek konum tabanl\u0131 analizler yapmak kolayla\u015f\u0131r. \u00d6rne\u011fin, bir \u015fehirdeki su\u00e7 olaylar\u0131n\u0131 harita \u00fczerinde g\u00f6rselle\u015ftirebilir veya farkl\u0131 b\u00f6lgelerdeki sat\u0131\u015f verilerini kar\u015f\u0131la\u015ft\u0131rabilirsiniz.<\/p>\n
Dash ile Karma\u015f\u0131k Uygulamalar Tasarlama: \u0130leri D\u00fczey Teknikler<\/h2>\n
Dash, Plotly taraf\u0131ndan geli\u015ftirilen bir Python k\u00fct\u00fcphanesidir. Streamlit'e k\u0131yasla daha karma\u015f\u0131k ve \u00f6zelle\u015ftirilebilir uygulamalar geli\u015ftirmek i\u00e7in idealdir. Dash, React.js tabanl\u0131 bir aray\u00fcze sahiptir ve bu sayede modern ve etkile\u015fimli uygulamalar tasarlamak m\u00fcmk\u00fcnd\u00fcr. Ancak, Streamlit'e g\u00f6re daha fazla kodlama bilgisi gerektirir.<\/p>\n
Dash ile bir uygulama olu\u015fturmak, genel olarak bir layout tan\u0131mlamak, callback fonksiyonlar\u0131 olu\u015fturmak ve bunlar\u0131 bir araya getirmekten ibarettir. Layout, uygulaman\u0131n kullan\u0131c\u0131 aray\u00fcz\u00fcn\u00fc tan\u0131mlar. Callback fonksiyonlar\u0131 ise, kullan\u0131c\u0131 etkile\u015fimlerine (\u00f6rne\u011fin, bir d\u00fc\u011fmeye t\u0131klama) yan\u0131t olarak uygulaman\u0131n davran\u0131\u015f\u0131n\u0131 belirler.<\/p>\n
import dash\nfrom dash import dcc\nfrom dash import html\nfrom dash.dependencies import Input, Output\nimport plotly.express as px\nimport pandas as pd\n\napp = dash.Dash(__name__)\n\n# \u00d6rnek veri k\u00fcmesi\ndf = pd.DataFrame({\n \"Fruit\": [\"Apples\", \"Oranges\", \"Bananas\", \"Apples\", \"Oranges\", \"Bananas\"],\n \"Amount\": [4, 1, 2, 2, 4, 5],\n \"City\": [\"SF\", \"SF\", \"SF\", \"Montreal\", \"Montreal\", \"Montreal\"]\n})\n\napp.layout = html.Div(children=[\n html.H1(children='Dash \u00d6rne\u011fi'),\n\n dcc.Graph(\n id='example-graph',\n figure=px.bar(df, x=\"Fruit\", y=\"Amount\", color=\"City\", barmode=\"group\")\n )\n])\n\nif __name__ == '__main__':\n app.run_server(debug=True)<\/pre>\n<\/code><\/p>\n
Bu \u00f6rnekte, Plotly Express kullanarak bir s\u00fctun grafi\u011fi olu\u015fturuyoruz ve Dash aray\u00fcz\u00fcyle entegre ediyoruz. Daha karma\u015f\u0131k uygulamalar i\u00e7in, Dash'in callback mekanizmas\u0131n\u0131 kullanarak, kullan\u0131c\u0131 etkile\u015fimlerine dinamik olarak yan\u0131t verebilirsiniz.<\/p>\n
Dash Uygulamalar\u0131nda Performans Optimizasyonu Nas\u0131l Sa\u011flan\u0131r?<\/h3>\n
Dash uygulamalar\u0131n\u0131n performans\u0131n\u0131 optimize etmek i\u00e7in, verileri \u00f6nceden i\u015fleyebilir, gereksiz i\u015flemleri azaltabilir ve verimli veri yap\u0131lar\u0131n\u0131 kullanabilirsiniz. Ayr\u0131ca, uygulaman\u0131n farkl\u0131 bile\u015fenlerini ba\u011f\u0131ms\u0131z olarak y\u00fckleyerek, uygulaman\u0131n ba\u015flang\u0131\u00e7 s\u00fcresini k\u0131saltmak m\u00fcmk\u00fcnd\u00fcr.<\/p>\n
Bokeh ile \u0130leri D\u00fczey Grafikler Olu\u015fturma: \u00d6zel G\u00f6rselle\u015ftirmeler<\/h2>\n
Bokeh, Python tabanl\u0131 etkile\u015fimli g\u00f6rselle\u015ftirmeler olu\u015fturmak i\u00e7in g\u00fc\u00e7l\u00fc bir k\u00fct\u00fcphanedir. \u00d6zellikle b\u00fcy\u00fck veri k\u00fcmeleri i\u00e7in optimize edilmi\u015ftir ve y\u00fcksek performansl\u0131 grafikler olu\u015fturman\u0131za olanak sa\u011flar. Bokeh, JavaScript ile taray\u0131c\u0131da \u00e7al\u0131\u015fan etkile\u015fimli grafikler olu\u015fturur. Bu sayede, b\u00fcy\u00fck veri k\u00fcmelerini bile h\u0131zl\u0131 ve ak\u0131c\u0131 bir \u015fekilde g\u00f6rselle\u015ftirebilirsiniz.<\/p>\n
Bokeh'in temel kullan\u0131m\u0131, verileri tan\u0131mlamak, grafik t\u00fcr\u00fcn\u00fc se\u00e7mek ve ard\u0131ndan grafi\u011fi g\u00f6r\u00fcnt\u00fclemekten ibarettir.<\/p>\n
from bokeh.plotting import figure, show, output_file\nfrom bokeh.models import ColumnDataSource\nimport pandas as pd\n\n# \u00d6rnek veri k\u00fcmesi\ndata = {'x': [1, 2, 3, 4, 5], 'y': [6, 7, 2, 4, 5]}\ndf = pd.DataFrame(data)\nsource = ColumnDataSource(df)\n\n# Grafik olu\u015fturma\np = figure(title=\"Bokeh \u00d6rne\u011fi\", x_axis_label='X', y_axis_label='Y')\np.circle(x='x', y='y', source=source, size=10, color=\"navy\", alpha=0.5)\n\n# Grafik g\u00f6sterme\noutput_file(\"bokeh_example.html\")\nshow(p)<\/pre>\n<\/code><\/p>\n
Bu kod blo\u011fu, basit bir daire grafi\u011fi olu\u015fturur. Bokeh, \u00e7e\u015fitli grafik t\u00fcrlerini destekler ve ayr\u0131ca grafiklerin \u00f6zelle\u015ftirilmesi i\u00e7in geni\u015f bir se\u00e7enek sunar.<\/p>\n
Bokeh ile \u00d6zelle\u015ftirilmi\u015f Grafik Olu\u015fturma Teknikleri Nelerdir?<\/h3>\n
Bokeh'in g\u00fcc\u00fc, \u00f6zelle\u015ftirme se\u00e7eneklerinde yatmaktad\u0131r. \u00d6zel grafikler olu\u015fturmak i\u00e7in, Bokeh'in geni\u015f bir ara\u00e7 setini kullanabilirsiniz. \u00d6rne\u011fin, grafiklere interaktif elemanlar ekleyebilir, renk \u015femalar\u0131n\u0131 de\u011fi\u015ftirebilir ve \u00f6zel etiketlemeler kullanabilirsiniz.<\/p>\n
\u00d6\u011frenme Yol Haritas\u0131<\/h2>\n
Yeni Ba\u015flayanlar:<\/strong><\/p>\n* Streamlit'in temel fonksiyonlar\u0131n\u0131 \u00f6\u011frenerek basit uygulamalar olu\u015fturmaya odaklan\u0131n. Basit grafikler ve veri tablolar\u0131 ile ba\u015flay\u0131n.
\n* Dash'in temel yap\u0131s\u0131n\u0131 (layout ve callback'ler) anlamak i\u00e7in basit \u00f6rnekler inceleyin.
\n* Bokeh'in basit grafik t\u00fcrlerini \u00f6\u011frenerek, k\u00fc\u00e7\u00fck veri k\u00fcmeleri \u00fczerinde \u00e7al\u0131\u015f\u0131n.<\/p>\n
Orta Seviye:<\/strong><\/p>\n* Streamlit'te daha geli\u015fmi\u015f widget'lar\u0131 kullanarak etkile\u015fimli uygulamalar olu\u015fturun.
\n* Dash'te callback fonksiyonlar\u0131 ile kullan\u0131c\u0131 etkile\u015fimlerini y\u00f6netmeyi \u00f6\u011frenin.
\n* Bokeh'te farkl\u0131 grafik t\u00fcrlerini kullanarak daha karma\u015f\u0131k g\u00f6rselle\u015ftirmeler yap\u0131n. Veri manip\u00fclasyonu tekniklerini geli\u015ftirin.<\/p>\n
\u0130leri Seviye:<\/strong><\/p>\n* Streamlit'te b\u00fcy\u00fck veri k\u00fcmeleriyle \u00e7al\u0131\u015fmak i\u00e7in performans optimizasyon tekniklerini uygulay\u0131n. Kendi \u00f6zel widget'lar\u0131n\u0131z\u0131 olu\u015fturun.
\n* Dash'te daha b\u00fcy\u00fck ve karma\u015f\u0131k uygulamalar geli\u015ftirerek, performans optimizasyonu ve hata y\u00f6netimi konusunda uzmanla\u015f\u0131n.
\n* Bokeh ile \u00f6zel grafikler olu\u015fturarak, uygulama tasar\u0131mlar\u0131nda ileri d\u00fczey teknikleri kullan\u0131n. JavaScript entegrasyonunu \u00f6\u011frenin.<\/p>\n
Ger\u00e7ek D\u00fcnya Senaryolar\u0131: Vaka Analizleri<\/h2>\n
* Streamlit:<\/strong> Bir e-ticaret \u015firketinin g\u00fcnl\u00fck sat\u0131\u015f verilerini g\u00f6rselle\u015ftirmek ve analiz etmek i\u00e7in h\u0131zl\u0131 bir uygulama olu\u015fturmak.
\n* Dash:<\/strong> Bir finans kurulu\u015funun portf\u00f6y performans\u0131n\u0131 g\u00f6steren karma\u015f\u0131k ve etkile\u015fimli bir dashboard geli\u015ftirmek.
\n* Bokeh:<\/strong> Bir bilimsel ara\u015ft\u0131rmada, milyonlarca veri noktas\u0131n\u0131 i\u00e7eren bir veri k\u00fcmesini y\u00fcksek performansl\u0131 bir \u015fekilde g\u00f6rselle\u015ftirmek.<\/p>\nPerformans Kar\u015f\u0131la\u015ft\u0131rmas\u0131<\/h2>\n
| \u00d6zellik | Streamlit | Dash | Bokeh |
\n|-----------------|-----------------------|-----------------------|-----------------------|
\n| Geli\u015ftirme H\u0131z\u0131 | \u00c7ok H\u0131zl\u0131 | Orta | Orta |
\n| \u00d6zelle\u015ftirme | Orta | Y\u00fcksek | Y\u00fcksek |
\n| Performans (B\u00fcy\u00fck Veri) | Orta | Y\u00fcksek | Y\u00fcksek |
\n| Karma\u015f\u0131kl\u0131k | D\u00fc\u015f\u00fck | Y\u00fcksek | Orta |<\/p>\n
G\u00fcvenlik Uyar\u0131lar\u0131<\/h2>\n
Dikkat:<\/strong> Uygulamalar\u0131n\u0131zda hassas veriler kullan\u0131yorsan\u0131z, g\u00fcvenlik a\u00e7\u0131klar\u0131n\u0131 \u00f6nlemek i\u00e7in gerekli \u00f6nlemleri alman\u0131z son derece \u00f6nemlidir. Verileri do\u011frulama, yetkilendirme ve \u015fifreleme gibi g\u00fcvenlik mekanizmalar\u0131n\u0131 uygulamay\u0131 unutmay\u0131n. Daha fazla bilgi i\u00e7in (https:\/\/fatihsoysal.com) inceleyebilirsiniz.<\/p>\nSonu\u00e7<\/h2>\n
Streamlit, Dash ve Bokeh, veri g\u00f6rselle\u015ftirme i\u00e7in g\u00fc\u00e7l\u00fc ara\u00e7lard\u0131r. Hangi arac\u0131 se\u00e7ece\u011finiz, projenizin karma\u015f\u0131kl\u0131\u011f\u0131na, ihtiya\u00e7lar\u0131n\u0131za ve deneyim seviyenize ba\u011fl\u0131d\u0131r. Bu makalede, her \u00fc\u00e7 araca da genel bir bak\u0131\u015f sunarak, se\u00e7im yapman\u0131z\u0131 kolayla\u015ft\u0131rmay\u0131 ama\u00e7lad\u0131k.<\/p>\n
S\u0131k\u00e7a Sorulan Sorular<\/h3>\n
1. Hangi ara\u00e7 en kolay \u00f6\u011frenilendir?<\/strong> Streamlit, yeni ba\u015flayanlar i\u00e7in en kolay \u00f6\u011frenilen ara\u00e7t\u0131r.<\/p>\n2. Hangi ara\u00e7 en y\u00fcksek performans\u0131 sunar?<\/strong> B\u00fcy\u00fck veri k\u00fcmeleri i\u00e7in Bokeh ve Dash genellikle daha iyi performans g\u00f6sterir.<\/p>\n3. Hangi ara\u00e7 en fazla \u00f6zelle\u015ftirme se\u00e7ene\u011fi sunar?<\/strong> Dash ve Bokeh, daha fazla \u00f6zelle\u015ftirme se\u00e7ene\u011fi sunar.<\/p>\n4. Bu ara\u00e7lar hangi programlama dillerini kullan\u0131r?<\/strong> \u00dc\u00e7\u00fc de Python tabanl\u0131d\u0131r.<\/p>\n5. Bu ara\u00e7lar\u0131n \u00fccretsiz ve a\u00e7\u0131k kaynak kodlu olmas\u0131 ne anlama geliyor?<\/strong> Bu, ara\u00e7lar\u0131 \u00fccretsiz olarak indirip kullanabilece\u011finiz ve kaynak kodlar\u0131na eri\u015febilece\u011finiz anlam\u0131na gelir. Bu, ara\u00e7lar\u0131n geli\u015ftirilmesine katk\u0131da bulunman\u0131z\u0131 sa\u011flar.<\/p>\nYazar: Fatih Soysal<\/p>\n","protected":false},"excerpt":{"rendered":"Modern Veri G\u00f6rselle\u015ftirme Ara\u00e7lar\u0131: Streamlit, Dash ve Bokeh’e Kapsaml\u0131 Bir Bak\u0131\u015f Veri \u00e7a\u011f\u0131nda ya\u015f\u0131yoruz ve bu verinin anlam\u0131n\u0131…","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-29619","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-genel","7":"cs-entry","8":"cs-video-wrap"},"yoast_head":"\n
Modern Veri G\u00f6rselle\u015ftirme Ara\u00e7lar\u0131: Streamlit, Dash ve Bokeh'e Kapsaml\u0131 Bir Bak\u0131\u015f<\/title>\n<meta name=\"description\" content=\"Veri \u00e7a\u011f\u0131nda ya\u015f\u0131yoruz ve bu verinin anlam\u0131n\u0131 \u00e7\u0131karabilmek, i\u015f kararlar\u0131 almak i\u00e7in hayati \u00f6nem ta\u015f\u0131yor. Ancak, ham veriler genellikle anla\u015f\u0131lmas\u0131 zor ve karma\u015f\u0131k olabilir. \u0130\u015fte bu noktada, veri g\u00f6rselle\u015ftirme ara\u00e7lar\u0131 devreye giriyor. Streamlit, Dash ve Bokeh gibi modern ara\u00e7lar, karma\u015f\u0131k verileri etkileyici ve anla\u015f\u0131l\u0131r g\u00f6rsellerle sunarak, verilerden de\u011fer \u00e7\u0131karmay\u0131 kolayla\u015ft\u0131r\u0131yor. Bu makalede, bu \u00fc\u00e7 g\u00fc\u00e7l\u00fc arac\u0131 detayl\u0131 olarak inceleyece\u011fiz ve hangi senaryolar i\u00e7in en uygun oldu\u011funu belirleyece\u011fiz.\" \/>\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\/modern-veri-gorsellestirme-araclari-streamlit-dash-ve-bokehe-kapsamli-bir-bakis\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Modern Veri G\u00f6rselle\u015ftirme Ara\u00e7lar\u0131: Streamlit, Dash ve Bokeh'e Kapsaml\u0131 Bir Bak\u0131\u015f\" \/>\n<meta property=\"og:description\" content=\"Veri \u00e7a\u011f\u0131nda ya\u015f\u0131yoruz ve bu verinin anlam\u0131n\u0131 \u00e7\u0131karabilmek, i\u015f kararlar\u0131 almak i\u00e7in hayati \u00f6nem ta\u015f\u0131yor. Ancak, ham veriler genellikle anla\u015f\u0131lmas\u0131 zor ve karma\u015f\u0131k olabilir. \u0130\u015fte bu noktada, veri g\u00f6rselle\u015ftirme ara\u00e7lar\u0131 devreye giriyor. Streamlit, Dash ve Bokeh gibi modern ara\u00e7lar, karma\u015f\u0131k verileri etkileyici ve anla\u015f\u0131l\u0131r g\u00f6rsellerle sunarak, verilerden de\u011fer \u00e7\u0131karmay\u0131 kolayla\u015ft\u0131r\u0131yor. 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