Python tools for data visualization — PyViz 0.0.1 documentation
Python tools for data visualization¶ Welcome to PyViz! The PyViz.org website is an open platform for helping users decide on the best open-source (OSS) Python data visualization tools for their purposes, with links, overviews, comparisons, and examples. Contents: Overviews of the OSS visualization packages available in Python, how they relate to each other, and the core concepts that underlie them
Facets - Visualizations for ML datasets
The power of machine learning comes from its ability to learn patterns from large amounts of data. Understanding your data is critical to building a powerful machine learning system. Facets contains two robust visualizations to aid in understanding and analyzing machine learning datasets. Get a sense of the shape of each feature of your dataset using Facets Overview, or explore individual observat
データå¯è¦–化ãƒãƒ¼ãƒˆã‚·ãƒ¼ãƒˆ - Qiita
Deleted articles cannot be recovered. Draft of this article would be also deleted. Are you sure you want to delete this article? ã¯ã˜ã‚㫠データå¯è¦–化ã§ã¯ã€ãƒ‡ãƒ¼ã‚¿ã®æ€§è³ªã«ã‚ˆã£ã¦æ¦‚ãã©ã®ã‚ˆã†ãªå¯è¦–化ãŒã§ãã‚‹ã®ã‹æ±ºã¾ã‚‹å ´åˆãŒã‚ã‚Šã¾ã™ã€‚データå¯è¦–化ã¯æŽ¢ç´¢çš„ãªãƒ‡ãƒ¼ã‚¿åˆ†æžã‚’ã™ã‚‹å ´åˆã‚„ã€ãƒ‡ãƒ¼ã‚¿åˆ†æžã—ãŸçµæžœã‚’誰ã‹ã«ä¼ãˆã‚‹ãŸã‚ã«é‡è¦ã§ã‚ã‚Šã€ãã®æ™‚々ã®ç›®çš„ã«åˆã‚ã›ãŸå¯è¦–化をé¸æŠžã™ã‚‹ã¹ãã§ã™ãŒã€ãã‚‚ãã‚‚å¯è¦–化手法ã®ç‰¹æ€§ã¨ãƒ‡ãƒ¼ã‚¿ã®æ€§è³ªãŒã‚ã£ã¦ã„ãªã„ã¨ã‚ã¾ã‚ŠåŠ¹æžœãŒãªã„å ´åˆãŒã‚ã‚Šã¾ã™ã€‚ç†è€…ãŒæ¥å‹™ã«ãŠã„ã¦ãƒ‡ãƒ¼ã‚¿å¯è¦–化ã™ã‚‹éš›ã«ãƒ‡ãƒ¼ã‚¿ã®æ€§è³ªã‹ã‚‰å¯è¦–化手法を導ãå ´åˆã®é“ã®ã‚Šã‚’æ•´ç†ã—ã€ãƒãƒ¼ãƒˆã‚·ãƒ¼ãƒˆã¨ã—ã¦ã¾ã¨ã‚ã¦ã¿ã¾ã—ãŸã€‚ ã‚‚ã¡ã‚ã‚“ã€èª¿ã¹ãŸã„・表ç¾ã—ãŸã„内容ã«ã‚ˆã£ã¦è‡ªåˆ†ã§è‡ªç”±ã«é¸ã‚“ã§ã‚‚ã¾ã£ãŸãå•é¡Œç„¡
Rã§è§£æžï¼šãƒ‡ãƒ¼ã‚¿ã®ç‰¹å¾´ã‚’一気ã«ç¢ºèªã€‚「GGallyã€ãƒ‘ッケージ
「ggplot2ã€ãƒ‘ッケージを利用ã—ã¦å¤šå¤‰æ•°ã®ç‰¹å¾´ã‚’プãƒãƒƒãƒˆã™ã‚‹ã“ã¨ãŒã§ãるパッケージã®ç´¹ä»‹ã§ã™ã€‚データã®è§£é‡ˆã«éžå¸¸ã«ä¾¿åˆ©ãªãƒ‘ッケージã‹ã¨æ€ã„ã¾ã™ã€‚ã¾ãŸã€è¤‡æ•°ã®ggplotオブジェクトã®ãƒ—ãƒãƒƒãƒˆãŒå¯èƒ½ãªã€Œggmatrixã€ã‚³ãƒžãƒ³ãƒ‰ã‚‚åŽéŒ²ã•ã‚Œã¦ã„ã¾ã™ã€‚ パッケージãƒãƒ¼ã‚¸ãƒ§ãƒ³ã¯2.1.2。実行コマンドã¯windows 11ã®R version 4.1.2ã§ç¢ºèªã—ã¦ã„ã¾ã™ã€‚ #パッケージの読み込み library("GGally") ###データ例の作成##### n <- 50 TestData <- data.frame(Group = sample(pas
Python spyre ã«ã‚ˆã‚‹ãƒ‡ãƒ¼ã‚¿åˆ†æžçµæžœã®Webアプリ化 - StatsFragments
R を使ã£ã¦ã„ã‚‹æ–¹ã¯ã”å˜çŸ¥ã ã¨æ€ã†ãŒã€R ã«ã¯ {Shiny} ã¨ã„ã†ãƒ‘ッケージãŒã‚ã‚Šã€ãƒ‡ãƒ¼ã‚¿åˆ†æžã®çµæžœã‚’ インタラクティブ㪠Web アプリã¨ã—ã¦å…±æœ‰ã™ã‚‹ã“ã¨ãŒã§ãる。{Shiny} ã£ã¦ä½•ï¼Ÿã¨ã„ã†æ–¹ã«ã¯ ã“ã¡ã‚‰ã®èª¬æ˜ŽãŒã‚ã‹ã‚Šã‚„ã™ã„。 qiita.com Python ã§ã‚‚ {Shiny} ã®ã‚ˆã†ãªãŠæ‰‹è»½å¯è¦–化フレームワークãŒã‚ã‚‹ã¨ã„ã„よãã€ã¨ãŸã³ãŸã³è¨€ã‚ã‚Œã¦ã„ãŸã®ã ãŒã€spyre ã¨ã„ㆠãªã‚“ã‹ãã‚Œã£ã½ã„パッケージãŒã‚ã£ãŸã®ã§è§¦ã£ã¦ã¿ãŸã„。 github.com インストール pip ã§ã€‚ pip install dataspyre 使ã„æ–¹ ç¾æ™‚点㧠ドã‚ュメンテーションã¯ãªã„ ã®ã§ã€README 㨠examples ディレクトリを見る。サンプルã¨ã—ã¦æ ªä¾¡ã‚’å–å¾—ã—ã¦ãƒ—ãƒãƒƒãƒˆã™ã‚‹Webアプリを作ã£ã¦ã¿ãŸã„。spyre 㧠Webã‚¢ãƒ—ãƒªã‚’ä½œã‚‹æ‰‹é †ã¯ä»¥ä¸‹ã®3ã¤ã€‚ spyre.server.
metrogram
metrogram ã«ã¤ã„㦠metrogramã¯æ±äº¬ã®åœ°ä¸‹é‰„ã«é–¢ã™ã‚‹ãƒ‡ãƒ¼ã‚¿ï¼ˆè·¯ç·š/ä½ç½®/時刻表ãªã©ã®æƒ…å ±ï¼‰ã‚’ã‚‚ã¨ã«ã€æ™®æ®µè¦‹ã‚‹äº‹ã®å‡ºæ¥ãªã„人ã¨é›»è»Šã®æµã‚Œã‚’視覚的ã«ã¨ã‚‰ãˆã‚‹ãƒ—ãƒã‚¸ã‚§ã‚¯ãƒˆã§ã™ã€‚ ※ å„データã¯2014å¹´9月時ã®ã‚’利用ã—ã¦ãŠã‚Šã€å¿…ãšã—ã‚‚ç¾çŠ¶ã®åœ°ä¸‹é‰„状æ³ã‚’æ£ç¢ºã«ã«å†ç¾ã—ã¦ã„る訳ã§ã¯ã‚ã‚Šã¾ã›ã‚“。 created by nulldesign.jp at 2014.09.11
鉄é“路線データをグラフã¨ã—ã¦Cytoscapeã§å¯è¦–化ã™ã‚‹ 1 - Qiita
Deleted articles cannot be recovered. Draft of this article would be also deleted. Are you sure you want to delete this article? ã“ã®ã‚·ãƒªãƒ¼ã‚ºã¯ã€Cytoscapeを使ã£ã¦ã‚„IPython Notebookã€Pandasãªã©ã®ã‚ªãƒ¼ãƒ—ンソースツールを利用ã—ã€å…¬é–‹ãƒ‡ãƒ¼ã‚¿ã‚’å…ƒã«å®Ÿéš›ã®ã‚°ãƒ©ãƒ•å¯è¦–化を行ã†éŽç¨‹ã‚’紹介ã™ã‚‹ã€å¯è¦–化ã®å®Ÿè·µè€…å‘ã‘ã®è¨˜äº‹ã§ã™ã€‚ 第一回 第二回 第三回 第四回 グラフå¯è¦–化ソフトCytoscapeã«ã‚ˆã‚‹åœ°ç†æƒ…å ±ãƒ‡ãƒ¼ã‚¿ã®å¯è¦–化 (Cytoscapeã«ã‚ˆã‚‹æ±äº¬å‘¨è¾ºã®è·¯ç·šå›³å¯è¦–化。ãƒã‚¤ãƒ¬ã‚¾ç‰ˆã¯ã“ã¡ã‚‰) ã¯ã˜ã‚ã« ç¾ä»£ã®åœ°å›³ã¯ã‚°ãƒ©ãƒ•ã§ã™ã€‚ãã‚‚ãã‚‚æ•°å¦çš„グラフã®ç ”究ã¯ç¾å®Ÿä¸–ç•Œã®çµŒè·¯å•é¡Œã‹ã‚‰å§‹ã¾ã‚Šã¾ã—ãŸ(ケーニヒスベルクã®å•é¡Œ)。計算機科å¦ã‚’å°‚æ”»ã—ãŸæ–¹ã¯ã€å¦ç”Ÿæ™‚代
A Layered Grammar of Graphics
Please see the online version of this article for supplementary materials. A Layered Grammar of Graphics Hadley WICKHAM A grammar of graphics is a tool that enables us to concisely describe the components of a graphic. Such a grammar allows us to move beyond named graphics (e.g., the “scat- terplotâ€) and gain insight into the deep structure that underlies statistical graphics. This article builds
Rickshaw: A JavaScript toolkit for creating interactive time-series graphs
Rickshaw is a JavaScript toolkit for creating interactive time series graphs. Rickshaw on GitHub Graphing Toolkit Rickshaw provides the elements you need to create interactive graphs: renderers, legends, hovers, range selectors, etc. You put the pieces together. See Demo → Built on d3.js It's all based on d3 underneath, so graphs are drawn with standard SVG and styled with CSS. Customize all you l
NVD3
This project is an attempt to build re-usable charts and chart components for d3.js without taking away the power that d3.js gives you. This is a very young collection of components, with the goal of keeping these components very customizable, staying away from your standard cookie cutter solutions. View more examples » GitHub Repo Download d3.v3.js. This is the only required library for NVD3. Dow
ggplot | Home
ggplot from Å·hat ggplot is a plotting system for Python based on R's ggplot2 and the Grammar of Graphics. It is built for making profressional looking, plots quickly with minimal code. ggplot is easy to learn from ggplot import * ggplot(aes(x='date', y='beef'), data=meat) +\ geom_line() +\ stat_smooth(colour='blue', span=0.2) ggplot is fun ggplot(diamonds, aes(x='carat', y='price', color='cut')) +
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Selected R Packages, from RStudio
Exploratory
Apache Zeppelin
htmlwidgets for R - gallery
Datapad - 100% Autonomous AI Data Analyst
Grafana: The open and composable observability platform | Grafana Labs
GitHub - mwaskom/seaborn: Statistical data visualization in Python
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