[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-seo-573667-105":53,"doc-detail-573667-en":126},{"code":4,"msg":5,"data":6},0,"success",[7,14,19,24,29,34,39,44,49],{"id":8,"doc_module":9,"doc_module_name":10,"category_name":11,"show_sort_weight":12,"slug":13},11,1,"Template","Presentations",90,"presentations",{"id":15,"doc_module":9,"doc_module_name":10,"category_name":16,"show_sort_weight":17,"slug":18},12,"Resumes",80,"resumes",{"id":20,"doc_module":9,"doc_module_name":10,"category_name":21,"show_sort_weight":22,"slug":23},14,"Invoices",70,"invoices",{"id":25,"doc_module":9,"doc_module_name":10,"category_name":26,"show_sort_weight":27,"slug":28},15,"Posters",60,"posters",{"id":30,"doc_module":9,"doc_module_name":10,"category_name":31,"show_sort_weight":32,"slug":33},16,"Social Media",50,"social-media",{"id":35,"doc_module":9,"doc_module_name":10,"category_name":36,"show_sort_weight":37,"slug":38},17,"Forms",40,"forms",{"id":40,"doc_module":9,"doc_module_name":10,"category_name":41,"show_sort_weight":42,"slug":43},18,"Letters",30,"letters",{"id":45,"doc_module":9,"doc_module_name":10,"category_name":46,"show_sort_weight":47,"slug":48},21,"Paper Templates",5,"papers-templates",{"id":50,"doc_module":9,"doc_module_name":10,"category_name":51,"show_sort_weight":4,"slug":52},158,"General","general-158",{"code":4,"msg":54,"data":55},"ok",{"site_id":56,"language":57,"slug":58,"title":59,"keywords":60,"description":61,"schema_data":62,"social_meta":119,"head_meta":121,"extra_data":123,"updated_unix":125},105,"en","r-cheat-sheet-quick-reference","R Cheat Sheet - Quick Reference","","R Cheat Sheet provides a compact quick reference to core R syntax and common workflows, focusing on vectors, matrices, assignment, comments, selection, utilities, apply/lapply-style functions, and basic I/O. It also summarizes time series structures and classes (ts, zoo, xts, timeDate), popular statistical tests for stationarity, normality, randomness, and independence, plus decomposition and forecasting models (decompose, stl, arima, Holt-Winters, auto.arima, ets). It includes Quandl package usage for API access and data retrieval.",{"@graph":63,"@context":118},[64,80,101],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":51,"@type":70,"position":76},"https://docshare.wps.com/template/general/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/r-cheat-sheet-quick-reference/573667/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/r-cheat-sheet-quick-reference/573667.png","ImageObject",442,249,{"name":88,"@type":89},"AfterMidnight","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-10-16","2026-10-14",true,{"@type":98,"interactionType":99,"userInteractionCount":79},"InteractionCounter",{"@type":100},"ViewAction",{"@type":102,"mainEntity":103},"FAQPage",[104,110,114],{"name":105,"@type":106,"acceptedAnswer":107},"What basic operators and assignment patterns are summarized in this R cheat sheet?","Question",{"text":108,"@type":109},"It lists operators such as #, \u003C-, \u003C\u003C-, and v[1], plus comment and assignment forms like a \u003C- 1 and a \u003C\u003C- 10 (with a note that the latter is not recommended).","Answer",{"name":111,"@type":106,"acceptedAnswer":112},"Which time series classes and constructors are included?",{"text":113,"@type":109},"It covers ts(data, frequency), zoo(data, index), xts(data, index), and time-series constructors like tis(), irts(), and timeSeries(), describing their date/index handling.",{"name":115,"@type":106,"acceptedAnswer":116},"What kinds of statistical tests and modeling functions are provided?",{"text":117,"@type":109},"It includes tests such as adf.test, jarque.bera.test, kpss.test, pp.test, shapiro.test, ks.test, and various randomness/independence tests, along with modeling and forecasting functions like arima(), auto.arima(), ets(), HoltWinters(), decompose(), and stl().","https://schema.org",{"og:url":78,"og:type":120,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":122,"canonical":78},"index,follow",{"doc_id":124,"site_id":56},573667,1792113660,{"code":4,"msg":5,"data":127},{"doc_id":124,"user_id":128,"nickname":88,"user_avatar":129,"doc_module":9,"category_id":50,"category_name":51,"doc_title":59,"doc_description":61,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":79,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":79,"language":135,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":136,"faqs":137,"seo_title":138,"seo_description":61,"update_tm":139,"read_time":73},962090896061,"https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc","R Cheat Sheet  \nBasic Syntax  \n\\#  \n\u003C - or =  \n\u003C\u003C -  \nv[1]  \n*  \n%*%  \n/  \n%/%  \n%%  \nComments Assignment  \nGlobal Assignment First element in a vector Scalar Multiplication Matrix Multiplication Division  \nInteger Division Remainder  \nVector and Matrix Operations  \nConstruction  \nc ()  \ncbind()  \nrbind()  \nmatrix()  \nConcatenate Column Concatenate Row Concatenate Create matrix  \nExample  \n\\# This is not interpretted  \na \u003C - 1; b = 2  \na \u003C\u003C - 10 \\# Not recommended  \nv[1]  \nc(1,1)*c(1,1) \\# 1 1  c(1,1)%*%c(1,1) \\# 2  \n1/2 \\# 0.5   \n1%/%2 \\# 0  \n7%%6 \\# 1   \nv \u003C - c(1,2,3,4) \\# 1 2 3 4  \ncbind(v,v) \\# 2 Columns rbind(v,v) \\# 2 Rows   \nmat \u003C -matrix(v,nrow=2,ncol=2)  \nSelection  \nv [1 ]  \ntail (v ,1 ) mat [2 ,1 ]   \nmat [1 ,]  \nmat [,2 ]  v [ c (1 , 3 )]  \nv [-c(1 , 3 )]  mat [, c (1 ,2 )]  \nmat [,1:5]   \nmat [“col”]  \nUtility  \nlength()  \ndim()  \nsort ()  \norder()  \nnames ()  \nSelect first  \nSelect last  \nSelect row 2, column 1  \nSelect row 1  \nSelect column 2  \nSelect the first and third values Select all but the first and third values Select columns 1 and 2  \nSelect columns 1 to 5  \nSelect column named “col”  \nLength of vector  \nDimensions of vector/matrix/dataframe Sorts vector  \nIndex to sort vector e.g. sort(v) == v[order(v)] Names of columns  \n1  \n[www. quandl. com](www. quandl. com)  \nApply  \napply (data , axis , fun)  \nlapply (data , fun)  \nrapply (data , fun , how)  \nApply the function fun to data along axis  \nApply the function fun to the list or vector data  \nApply the function fun to data depending on the value of how  \nFor a great introduction to using apply see this article.  \nI/O  \nread.table (“filename”, sep=”,”) read.csv ()  \nfromJSON ()  \nxmlTreeParse ()  \nwrite.csv ()  \nStructures  \ndata.frame (…)  \nlist ( name=var )  \nts (data , frequency)   \nTime Series  \nTime Series Classes  \nts (data , frequency)  \nzoo (data , index)  \nxts (data , index)  \ntis()  \nirts()   \ntimeSeries ()  \nReads information in from file with a variable delimiter Read csv file into dataframe  \nRead JSON formatted file or string into a list  \nRead XML formatted file or string into a list  \nWrites a dataframe or matrix (or tries to convert input to one) and writes to csv  \nTakes multiple variables with the same number of rows and creates a dataframe R’s implementation of a hash, takes multiple variables or variable tag pairs Creates a regularly spaced time series object  \nFrom R base, handles regularly spaced time series  \nPart of the zoo package, handles irregularily spaced data using arbitrary time date classes  \nModification to zoo, gives more power to selecting date subsets Uses POSIXct time stamps  \nFrom the package tseries and uses POSIXct time stamps Uses timeDate time stamps  \nTests  \nadf.test  \njarque.bera.test  \nkpss.test  \npo.test  \npp.test  \nruns .test  \nterasvirta.test  \nwhite.test  \nbox.test  \nComputes the Augmented Dickey-Fuller test for the null that the series has a unit root  \nTests the null of normaility for the series using the Jarque-Bera test statistics Computes the KPSS test for the null that the series is level or trend stationary Computes the Phillips-Ouliaris test for the null that the series in not cointegrated Computes the Phillips-Perron test for the null that the series has a unit root Computes the runs test for randomness of the binary series  \nGenerically computes Teraesvirta’s neural network test for neglected nonlinearity for the time series  \nGenerically computes the White neural network test for neglected nonlinearity for the time series  \nCompute the Box-Pierce or Ljung-Box test statistics for examining the null of independence in a given series  \n2  \n[www. quandl. com](www. quandl. com)  \nshapiro.test  \nks.test  \npunitroot  \nDecomposition  \ndecompose()  \nfilter()  \nstl()  \nModels  \nar ()  \nma ()  \narima()  \nauto.arima()  \nets ()  \nHoltWinters ()  \nforcast (model , n)  \nUtility  \nindex()  \ncoredata() lag (ts , n)  diff (ts , n)  \nacf() or Acf ()  pacf() or Pacf ()  \nndiff()  accuracy ()  \nTest for normalit","cbCaiaZ6s3gNBNlx","https://ap.wps.com/l/cbCaiaZ6s3gNBNlx","pdf",210084,"English","# Basic Syntax\n## Comments and Assignment\n## Vector and Matrix Operations\n## Selection and Utility\n# Apply and I/O\n## Apply family\n## I/O functions\n# Data Structures and Time Series\n## data.frame and list\n## Time Series classes\n# Tests and Decomposition\n## Stationarity and distribution tests\n## Decomposition and filtering\n# Models and Quandl\n## AR/MA/ARIMA and forecasting\n## Quandl package and authentication","[{\"question\":\"What basic operators and assignment patterns are summarized in this R cheat sheet?\",\"answer\":\"It lists operators such as #, \\u003c-, \\u003c\\u003c-, and v[1], plus comment and assignment forms like a \\u003c- 1 and a \\u003c\\u003c- 10 (with a note that the latter is not recommended).\"},{\"question\":\"Which time series classes and constructors are included?\",\"answer\":\"It covers ts(data, frequency), zoo(data, index), xts(data, index), and time-series constructors like tis(), irts(), and timeSeries(), describing their date/index handling.\"},{\"question\":\"What kinds of statistical tests and modeling functions are provided?\",\"answer\":\"It includes tests such as adf.test, jarque.bera.test, kpss.test, pp.test, shapiro.test, ks.test, and various randomness/independence tests, along with modeling and forecasting functions like arima(), auto.arima(), ets(), HoltWinters(), decompose(), and stl().\"}]","R Cheat Sheet - Quick Reference | PDF",1791943971]