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DataScience’s Diary
R 的字元處理函數 paste - DataScience’s Diary
http://datascience.hatenadiary.com/entry/2014/08/24/175431
Login to quote this blog. Failed to save quote. Please try again later. You cannot quote because this article is private. 最近對文字資料探勘(text mining)特別感到興趣,因此,今天就來談談 R 的字元處理。 大家都知道 R 中處理字元最常用的函數就屬 paste 了。 其實 paste 有兩個重要參數 collapse 與sep,請先看下面的例子。 Paste("one", 2, "three", 4, "five"). 1] "one 2 three 4 five". Paste(c("one", "two", "three", "four"), collapse = " "). 1] "one two three four". 此函數也可將一字元向量(character vector)中的各元素(i.e. 各字串)串接起來,銜接字元以collapse 參數設定之。 Paste("X", 1:5, sep = " ). 1] "X1" "X2" "X3" "X4" "X5".
R軟體中的attach 與時下的 with 指令 - DataScience’s Diary
http://datascience.hatenadiary.com/entry/2014/08/24/174754
Login to quote this blog. Failed to save quote. Please try again later. You cannot quote because this article is private. R軟體中的attach 與時下的 with 指令. 最近在學會( http:/ www.r-software.org/. 的台灣 R 軟體使用者論壇上有人提起 attach 指令,讓我想起前一陣子看到的 with 指令。 過去我們常用 attach 指令,將資料框物件附加到搜尋路徑(search path)上,使得資料框中的變數對於 R 的直譯器(interpreter)而言是可見的(visible),省去須敲擊資料框全名方能引用變數的麻煩 以 car 套件中的資料框 Duncan 為例,. Type income education prestige. Accountant prof 62 86 82. Pilot prof 72 76 83. Architect prof 75 92 90. Author prof 55 90 76. Lm(prestige ...
2014-08-24
http://datascience.hatenadiary.com/entries/2014/08/24
Login to quote this blog. Failed to save quote. Please try again later. You cannot quote because this article is private. 但這樣說來,好像學 R 是件令人可懼的事,其實讀者們不用太擔心 因為 R 玩家中有許多強大的巨人會引領我們向前航行。 Plyr 套 件 ,就 是由多 產的 美國 Rice 大學統 計系助理 教授,紐西蘭裔的 Hadley Wickham( http:/ had.co.nz/. 所開發的,他是資料視覺化(data visualization)的專家,也是知名的資料整理(data manipulation)套件 reshape 與繪圖套件 ggplot2 的主要開發者。 Dd - data.frame(matrix(round(rnorm(216), 2), 72, 3), c(rep("A", 24), rep("B", 24), rep("C", 24) , c(rep("J", 36), rep("K", 36) ). V1 v2 v3 dim1 dim2.
好書介紹:Data Manipulation with R - DataScience’s Diary
http://datascience.hatenadiary.com/entry/2014/08/24/175708
Login to quote this blog. Failed to save quote. Please try again later. You cannot quote because this article is private. 好書介紹 Data Manipulation with R. Spector, Phil (2008), Data Manipulation with R, Springer. 證諸資料分析競賽中的優勝作品,資料探勘專案的關鍵成功因素是從正確的資料中繪製圖形,或建立適切的資料模型,而非一味地醉心於高階或奇特模型的配適工作。 因此,做好資料前處理的工作,方能提升資料品質,加大專案成功的機率。 否則,再先進的模型,都會淪為垃圾進垃圾出(garbage in garbage out)的不好結果。 全書範例實用,敘述簡單明瞭,實為欲精通 R 資料分析技術者必修的基本馬步。 撰文者:國立台北商業技術學院資訊與決策科學所教授、中華 R 軟體學會理事長 鄒慶士 博士. 好書介紹 Data Manipulation with R. 好書介紹 R in Action.
好書介紹:R in Action - DataScience’s Diary
http://datascience.hatenadiary.com/entry/2014/08/24/180439
Login to quote this blog. Failed to save quote. Please try again later. You cannot quote because this article is private. 好書介紹 R in Action. Kabacoff, Robert I. (2011), R in Action: Data Analysis and Graphics with R, Manning. 玩 R 的人大多知道 Quick-R: accessing the power of R 這個網站,此站不僅名稱 www.statmethods.net 令人印象深刻,且網頁組織與規劃得十分簡單明瞭,內容說明更是清楚易懂,是許多人入門 R 軟體的良伴。 網站主人 Robert I.Kabacoff 是心理學博士,不僅有 25 年的 SAS 與 SPSS 程式設計經驗,還精通多種程式語言。 如今 Kabacoff 博士根據 Quick-R 的網站內容加以擴編成為此本好書,全書共分四大部份十六章,以按步就班的方式介紹實際的資料分析與視覺化方法。
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資料科學部落格 - 中華R軟體學會
http://www.r-software.org/home/zi-liao-ke-xue-bu-luo-ge
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The Data Science Research Group at Politecnico di Milano
BIG DATA AND DATA SCIENCE. Is an emerging discipline that combines data management, machine learning, data analysis, statistics and mathematics, computational science, artificial intelligence, data visualization and user experience design to big data. Data scientists are engaged in developing methodologies, algorithms and software implementations for making data more accessible and useful. WHAT IS DATA SCIENCE? Data acquisition, representation, cleaning and integration;. Data visualization and exploration.
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DataScience’s Diary
好書介紹 R in Action. Kabacoff, Robert I. (2011), R in Action: Data Analysis and Graphics with R, Manning. 玩 R 的人大多知道 Quick-R: accessing the power of R 這個網站,此站不僅名稱 www.statmethods.net 令人印象深刻,且網頁組織與規劃得十分簡單明瞭,內容說明更是清楚易懂,是許多人入門 R 軟體的良伴。 網站主人 Robert I.Kabacoff 是心理學博士,不僅有 25 年的 SAS 與 SPSS 程式設計經驗,還精通多種程式語言。 他自認初接觸 R 時,因為 R 的廣博與強大,經常覺得自己無知與渺小,因而架設了 Quick-R 網站,分享個人的學習歷程,進而體驗 learning by teaching 的最佳功效。 如今 Kabacoff 博士根據 Quick-R 的網站內容加以擴編成為此本好書,全書共分四大部份十六章,以按步就班的方式介紹實際的資料分析與視覺化方法。 好書介紹 R in Action. 好書介紹 R through Excel.
Data Science - Università di Roma
Salta al contenuto principale. La Sapienza - Università di Roma. 2015 July 6-8: "porte aperte alla Sapienza". 2015, June 25: course presentation. Enrollment for the Academic Year 2015/2016. Online preselection application for non-EU students. Master's Degree in Data Science. The remarkable increase in the volume and complexity of available data. Learning techniques, algorithmic thinking. Department of Computer, Control and Management Engineering (DIAG). Meet the faculties of the Data Science Master. ...
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Politechnika Warszawska | Studia podyplomowe - Big Data, Data Science
Instytut Informatyki Politechniki Warszawskiej jest jedną z najstarszych w Polsce instytucji akademickich zajmujących się badaniami i nauczaniem m.in. w dziedzinie systemów informacyjnych. Nasze studia prowadzone są przez praktyków: osoby na co dzień stosujące narzędzia i metody analizy dużych zbiorów danych w celu rozwiązania konkretnych problemów. Algorytmy, narzędzia i aplikacje dla problemów typu Big Data. Przetwarzanie i analiza dużych zbiorów danych. Informacje o rekrutacji na studia:. Minimalna li...
KIT - Data Science -Startseite
News (Stellen, Konferenzen). Institute of Information Systems and Marketing (IISM). Tel: 49 721 608 4 8370. What is Data Science? How is Data Science different from Statistics? What makes Data Science attractive? Moreover, the increase in data available to firms has not been matched by a similar increase in individuals with the right mix of quantitative skills and business intelligence. In other words, firms are actively searching for data scientists and they pay good money to hire them. Additionally, on...
Data Science :: Home
Doctoral training in the theory and practice of data science at the University of Edinburgh. Data science is the study of the computational principles, methods, and systems for extracting knowledge from data. Large data sets are now generated by almost every activity in science, society, and commerce ranging from molecular biology to social media, from sustainable energy to health care. How can we efficiently find patterns in these vast streams of data? Check out some examples of the wide-ranging researc...