Jupyter and conda for R | Anaconda
tl; dr: We discuss the many benefits Jupyter, the IRKernel and conda can provide for data scientists working in R. Jupyter, previously called IPython, is already widely adopted by data scientists, researchers, and analysts. Jupyter’s notebook user interface enables mixing executable code with narrative text, equations, interactive visualizations, and images to enhance team collaboration and advanc
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Technical Data presentation in R コピペã§å¦ã¶ Rã§ãƒ†ã‚¯ãƒ‹ã‚«ãƒ«ãƒ‡ãƒ¼ã‚¿ãƒ—レゼンテーション １．基礎統計解æžç·¨ グラフィックス・リテラシï¼æ•™è‚²: ã€Œå›³å¦ I ãƒ»å›³å½¢æƒ…å ± I ・統計å¦ã€ç§‘目　修了後ã®ã‚³ãƒ¼ã‚¹ã‚¦ã‚§ã‚¢ ç¦å²¡å¤§å¦å·¥å¦éƒ¨å›³å¦æ•™å®¤ã€€ã€€ã€€æ¢¶å±±ã€€å–œä¸€éƒŽ ・ã¤ã¾ã¿é£Ÿã„ã§ï¼Œå¦ç¿’ã—ãªã„よã†ã«é¡˜ã„ã¾ã™ï¼Ž ・データã®å¯è¦–化を体系・系統ã ã£ãŸã‚¹ã‚ルã«ã™ã‚‹ãŸã‚ã«é †ã‚’追ã£ã¦å¦ç¿’ã™ã‚‹ï¼Ž ・統計ブームã«ä¹—ã£ã¦ã„ã‚‹å¦ç¿’者も先人ã«æ„Ÿè¬ã®æ°—æŒã¡ã‚’．ã•ã‚‰ã«ï¼Œ ・確ã‹ãªã‚¹ã‚ルã«ã™ã‚‹ãŸã‚ã«ï¼Œæ•™ç§‘書・解説書をç†è§£ã—，Rスクリプトã§ç¢ºèªï¼Ž A.　ã¯ã˜ã‚ã«--ã“ã“ã¯çµ±è¨ˆãƒ»è§£æžã®å¿…è¦ã‚’味ã‚ã£ãŸå¾Œã§èªã‚ã°ã‚ˆã„ ã¾ãšï¼Œçµ±è¨ˆã®æ‰‹ç¶šãを実行ã™ã‚‹ï¼Žæ…£ã‚ŒãŸã‚‰çµ±è¨ˆçš„ã«è€ƒãˆã‚ˆã†ï¼Ž å¦æ ¡ã®çµ±è¨ˆå¦ã‚’復習--è²·ã£ãŸæ•™ç§‘書ã¨ãƒŽãƒ¼ãƒˆã‚’ã¾ãŸèªã‚€ã ã‘ a. 測定ã¨å°ºåº¦ã€€Measurement and scale b. 記述統計å¦ã®
Debugging in R
These web pages describe various issues involved in debugging code written for the open source statistical package R. It is particularly aimed at Windows programmers, but many of the techniques work more widely. For instructions particular to other platforms, and non-compiler-specific details, see the Writing R Extensions manual in the docs subdirectory of the R installation. The cat() and print()
How can we make xkcd style graphs?
Apparently, folk have figured out how to make xkcd style graphs in Mathematica and in LaTeX. Can we do it in R? Ggplot2-ers? A geom_xkcd and/or theme_xkcd? I guess in base graphics, par(xkcd=TRUE)? How do I do it? As a first stab (and as much more elegantly shown below) in ggplot2, adding the jitter argument to a line makes for a great hand-drawn look. So - ggplot(mapping=aes(x=seq(1,10,.1), y=seq
Rmpiã¨snow㧠並列処ç†
This document discusses using Rmpi and snow packages in R to perform parallel computing on a Mac. It provides examples of using makeCluster with MPI, clusterExport, and parLapply to distribute calculations across multiple CPU cores. Metrics are given showing reduced computation time when using 4 cores versus a single core for sampling and sorting large datasets.Read less
foreach＋doSNOWパッケージを使ã£ã¦ã€ä¸¦åˆ—処ç†ã‚’ã‚„ã£ã¦ã¿ãŸ - My Life as a Mock Quant
ãªã‚“ã ã‹web屋界隈ã§ã¯Hadoopã ã®Mahoutã ã®è±¡ã‚’使ã†ã ã®ä½¿ã‚ãªã„ã ã®æ¥½ã—ãã†ãªäº‹ã‚’ã‚„ã£ã¦ã„ã¦ã€ç§ã¯ã¨ã¦ã‚‚ã•ã¿ã—ãã€ãã—ã¦ã†ã‚‰ã‚„ã¾ã—ãã‚‚ãªã£ãŸã‚ã‘ã§ã™ãŒæ‰‹å…ƒã«ãã‚“ãªç«‹æ´¾ãªç’°å¢ƒãªã‚“ã¦ãªã„ã‚ã‘ã§ã€‚ã—ã‹ã—ã€ãã‚“ãªç§ã«ã‚‚マルãƒã‚³ã‚¢ã®ãƒ‘ソコンãŒä¸Žãˆã‚‰ã‚Œã¦ã„ã‚‹ã®ã§ãã‚Œã§è¨ˆç®—ã®ä¸¦åˆ—化をやã£ã¦ã¿ãŸã€‚OSã¯windows XP(32bit)。 使ã†ã®ã¯çµ±è¨ˆæ•°ç†ç ”究所ã®ã‚»ãƒŸãƒŠãƒ¼ã§ãŠè–¦ã‚ã•ã‚Œã¦ã„ãŸforeachパッケージ*1。ã“ã‚Œã¯Revlution Rã®äººãŸã¡ãŒä½œã£ã¦ã„ã‚‹ã®ã§ä»Šå¾Œã¨ã‚‚継続的ãªé–‹ç™ºã¨é€²åŒ–ãŒæœŸå¾…ã§ãã‚‹ã¨ã®ã“ã¨ã€‚ã¾ãšã¯ã€doSNOWパッケージもåˆã‚ã›ã¦ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã€‚ install.packages("foreach") install.packages("doSNOW") foreachパッケージã§ã¯forループã®ä¸¦åˆ—化をã—ã¦ãれるã®ã§ã™ãŒã€å‡¦ç†ã‚’並列化ã•ã›ãªã„ã§æ›¸ãã“ã¨ã‚‚ã§ãã‚‹ã®ã§ã¾ãš
Rã®ã‚³ãƒ¼ãƒ‰ã‚’ multicore を使ã£ã¦ã€ãƒ†ã‚¹ãƒˆé§†å‹•é–‹ç™ºã§ãƒžãƒ«ãƒã‚³ã‚¢åŒ–ã™ã‚‹ã‚ˆ
multicore パッケージを利用ã—ã¦ãƒžãƒ«ãƒã‚³ã‚¢åŒ–ã—ã¦ã¿ã¾ã™ã€‚ã¨ã¯è¨€ã£ã¦ã‚‚ã€sapply, lapply ã‚’ mclapply ã«ã™ã‚‹ã ã‘ã®ç°¡å˜ãªãŠä»•äº‹ã§ã™ãŒã€ã›ã£ã‹ããªã®ã§ testthat を使ã£ã¦ãƒžãƒ«ãƒã‚³ã‚¢åŒ–ã™ã‚‹éš›ã«ãƒ†ã‚¹ãƒˆé§†å‹•é–‹ç™ºã§å®Ÿè£…ã—ã¦ã„ãã¾ã™ã€‚ ã¾ãšã¯ã€ãã®ã¸ã‚“ã®ã‚¢ãƒƒãƒ—ルストアã§è³¼å…¥å¯èƒ½ãª MacBook Air を購入ã—ã¾ã—ょã†ã€‚今回ã¯ã“ã‚Œã§ã‚„ã‚Šã¾ã™ã€‚Rã‚‚ Mac 版㮠dmg を普通ã«ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã—ã¾ã—ょã†ã€‚次ã«ãƒ‘ッケージをインストールã—ã¾ã™ã€‚ sudo R install.packages(multicore) install.packages(testthat) q() インストールãŒç°¡å˜ãªã®ãŒã‚ˆã„ã§ã™ã。MPIã¨ã‹ãã†ã„ã†ã‚‚ã®ã‚’ã”ã¡ã‚ƒã”ã¡ã‚ƒè¨å®šã™ã‚‹å¿…è¦ãªãªã„ã§ã™ã€‚ 今回ã¯éžæœ‰ç•ŒåŒºé–“ã®ãƒ¢ãƒ³ãƒ†ã‚«ãƒ«ãƒç©åˆ†ã«ã‚ˆã£ã¦ã€æ¨™æº–æ£è¦åˆ†å¸ƒã®ç´¯ç©åˆ†å¸ƒé–¢æ•°ã‚’計算ã—ã¾ã™ã€‚ã¾ãšã¯ for ã§
R + Bioconductor ã§éºä¼åæ§‹é€ ã‚’æã
From Evernote: Rã§éºä¼åæ§‹é€ ã‚’æã 超並列DNAシーケンサーã®ç™»å ´ã§ã€éºä¼åæ§‹é€ ãªã©ã€ã‚²ãƒŽãƒ 上ã®ã‚¤ãƒ™ãƒ³ãƒˆã‚„オブジェクトã®ãƒ‡ãƒ¼ã‚¿ã‚’大é‡ã«å¾—ã‚‹ã“ã¨ãŒã§ãるよã†ã«ãªã£ã¦ãã¾ã—ãŸã€‚データ解æžã«ã¨ã£ã¦å¯è¦–化ã¯é‡è¦ã§ã™ãŒã€ã‚²ãƒŽãƒ 上ã§èµ·ãã¦ã„るイベントãªã®ã§ã€ã‚²ãƒŽãƒ 上ã«é…ç½®ã—ã¦å¯è¦–化ã—ãŸã„å ´é¢ãŒã‚ˆãã§ã¦ãã¾ã™ã€‚ã—ã‹ã—ã€ã•ã¾ã–ã¾ãªã‚²ãƒŽãƒ 上ã®ã‚ªãƒ–ジェクトをゲノム座標ã‹ã‚‰ç”»åƒåº§æ¨™ã«å¤‰æ›ã—ã¦ã€çµµã‚’書ãã®ã¯æ„外ã¨é¢å€’ãªä½œæ¥ã§ã™ã€‚ 例ãˆã°éºä¼åæ§‹é€ ã®çµµã‚’書ã“ã†ã¨ã—ã¾ã™ã€‚ã“ã‚Œã¯ã€éºä¼åæ§‹é€ ã‚’ã©ã®ã‚ˆã†ã«å…¥æ‰‹ã™ã‚‹ã‹ã€éºä¼åæ§‹é€ ã‚’ã©ã®ã‚ˆã†ã«æãã‹ã€ã®2ã¤ã®å•é¡Œã«åˆ†ã‘ã‚‹ã“ã¨ãŒã§ãã¾ã™ã€‚ã“ã“ã§ã¯ã€éºä¼åæ§‹é€ ã®ãƒ‡ãƒ¼ã‚¿ã¯ã€R + Bioconductor ã® biomaRt パッケージを使ã£ã¦ã€Ensembl Biomart ã‹ã‚‰ãƒ€ã‚¦ãƒ³ãƒãƒ¼ãƒ‰ã™ã‚‹ã“ã¨ã§è§£æ±ºã—ã¾ã™ã€‚éºä¼åæ§‹é€ ã‚’ã©ã®ã‚ˆã†ã«æãã‹ã«ã¤ã„ã¦ã¯ã€Genome
Rデータフレーム自由自在
This document summarizes information about a person named Takeshi Arabiki. It includes: 1. Their Twitter handle is @a_bicky and ID is id:a_bicky. 2. A link to their blog on Hatena is provided. 3. They have written books and slides about using R and SciPy. 4. Links are provided to their slideshare presentations about using Twitter and R.Read less
R sp graphics example figures
(png graphs were made using the GDD driver in package GDD) For a general gallery on R graphics, see: R Graph Gallery : Enhance your data visualisation with R. fig01.R : coloured points plot with legend in plotting area and scales: fig02.R : coloured points plot with legend in plotting area and scales; non-default number of cuts with user-supplied legend entries: fig03.R : points plot with scale ba
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R ã§é«˜é€Ÿãª (ユークリッド) è·é›¢è¡Œåˆ—計算 | Atsushi TATSUMA Web Page
ã¯ã˜ã‚㫠皆ã•ã‚“㯠R 好ãã§ã™ã‹ï¼Ÿå¥½ãã§ã™ã‚ˆã。勉強会もãŸãã•ã‚“ã‚ã‚Šã¾ã™ã‚‚ã‚“ã。 僕ã¯å«Œã„ã§ã™ã€‚é…ã„ã®ã§ã€‚ã§ã‚‚ã€æ›¸ãæ–¹ã®å·¥å¤«ã§ãªã‚“ã¨ã‹ãªã‚‹ã“ã¨ã‚‚ã‚ã‚Šã¾ã™ã€‚ 僕ãŒç ”究室ã§ã‚„ã£ã¦ã‚‹ã“ã¨ã¯ã€è¡¨å‘ã検索ã¨ã„ã†ã“ã¨ã«ãªã£ã¦ã‚‹ã®ã§ã™ãŒã€ ã‚„ã£ã¦ã‚‹ã“ã¨ã¯ã€æ¬¡å…ƒå‰Šæ¸›ã¨ã‹ã‚¯ãƒ©ã‚¹ã‚¿ãƒªãƒ³ã‚°ã¨ã‹ã€ãã®ã‚ãŸã‚Šã§ã™ã€‚ データãŒãªã™ç©ºé–“ã‚’ã€è§£æžã™ã‚‹ã¨ã„ã†ç‚¹ã§ã¯ã€æ¤œç´¢ã‚‚機械å¦ç¿’も一緒ã§ã™ã。 ã“ã®ã€ãƒ‡ãƒ¼ã‚¿ãŒç©ºé–“上ã§ã©ã†ã„ã£ãŸæ„Ÿã˜ã«ãªã£ã¦ã‚‹ã®ã‹ã€ã®æ‰‹ãŒã‹ã‚Šã¨ãªã‚‹ãƒ¢ãƒŽã«ã€ 全データ点åŒå£«ã®è·é›¢ãŒã‚ã‚Šã¾ã™ã€‚ã“れを行列ã§è¡¨ã—ãŸã‚‚ã®ãŒã€è·é›¢è¡Œåˆ—ã§ã™ã€‚ è·é›¢ã«ã¯ã€ã ã„ãŸã„ã€ã¾ãšã¯ã€ãƒ¦ãƒ¼ã‚¯ãƒªãƒƒãƒ‰è·é›¢ã‚’試ã—ã¾ã™ã€‚ R ã§è·é›¢è¡Œåˆ—を求ã‚ã‚‹å ´åˆ dist 関数を使ã„ã¾ã™ãŒã€ ユークリッドè·é›¢ã ã‘ã«çµžã‚Œã°ã€è‡ªä½œã—ãŸé–¢æ•°ã®æ–¹ãŒé€Ÿããªã‚Šã¾ã™ã€‚ 2点間ã®ãƒ¦ãƒ¼ã‚¯ãƒªãƒƒãƒ‰è·é›¢ ã„ã¾ã€äºŒæ¬¡å…ƒã®ãƒ‡ãƒ¼ã‚¿ãŒã€äºŒç‚¹ã‚ã‚‹ã¨ã—ã¾ã™ã€‚ ã¡ãªã¿ã«ã€ãƒ‡ãƒ¼ã‚¿ç‚¹
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How do I set a CRAN mirrror to install an R package in Jupyter? · Issue #234 · IRkernel/IRkernel
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3D Plots with ggplot2 and Plotly
renjin - Project Hosting on Google Code
http://www.stat.auckland.ac.nz/~paul/RG2e/
NumPy for R (and S-Plus) users – Mathesaurus
How to Superimpose Histograms
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