跳出框擁抱非結(jié)構(gòu)化數(shù)據(jù)

>>12345>sapply(iris,>sapply(iris,>[1]5.04.44.9dimension>atomic??????dimension>atomic??????data>1>12>線性型非線線性型非線模機(jī)器習(xí)算…結(jié)構(gòu)化數(shù)Computer非結(jié)構(gòu)結(jié)構(gòu)化數(shù)Computer非結(jié)構(gòu)化數(shù)reading,music,moviessports,musicmovies,R:2,C#:4,R:3,Java:2,C++:51231234567111223312312312345671112233123456789111222333243325142[{"Name":"Ken","Age":24,["Expertise":"R":"CSharp":"Python":}]）--）----243#R=====#R=======)數(shù)據(jù)積累過(guò)根據(jù)數(shù)據(jù)積累過(guò)根據(jù)需要收集數(shù)全面收集數(shù)數(shù)據(jù)類型變{{}====-/typePerson{FirstName:stringLastName:stringBirthDate:DateTimeChildren:Personlist}letpersons=//...loadsomedataletavgAge=List.filter(funp->p.LastName=List.sortBy(funp->-List.averageBy(funp->(DateTime.Now-p.BirthDate).TotalDays/對(duì)對(duì)象中的元素進(jìn)行映射（mapping）提供一系列高階函數(shù)，可以方便地篩選（filtering）、分組（grouping）、排序（sorting）、合并（joining）（updating）、搜索（searching）以及其他常用操作對(duì)管道操作（pipeline）友好，方便非結(jié)構(gòu)化數(shù)據(jù)處理的流程化整合多種非結(jié)構(gòu)化數(shù)據(jù)源的讀寫(xiě)方法，方便接入數(shù)據(jù)源和輸出數(shù)合理利用R的元編程特性，簡(jiǎn)化使用Age:25Age:24Age>=25->list.filter(data,Age>=25->list.filter(data,Age>=25->Age:25Age:25Age:24當(dāng)envir當(dāng)envirlist時(shí)上一級(jí)符號(hào)搜索環(huán)境>.2135792>.2135792468>>>.>.012>.+555>ab>.+555>abc篩選list.filter,list.find,list.findi,list.first,list.take,list.skip,list.takeWhile,篩選list.filter,list.find,list.findi,list.first,list.take,list.skip,list.takeWhile,list.skipWhile,list.which,list.any,list.count,排序list.order,合并list.join,數(shù)據(jù)讀寫(xiě)list.parse,list.load,list.save, list.append,list.prepend,list.reverse,list.zip,list.rbind,list.cbind,list.stack,list.flatten,s,list.sample搜索 list.group,list.ungroup,list.cases,list.class,mon,更新 分 函映射 list.map,list.mapv,list.select,list.iter,:…::…:============================sample(sizesample(size=10000,replace=TRUE),density(kernel="gaussian"),plot(col="red",main="densitympgsample(size=10000,replace=TRUE)density(kernel="gaussian")plot(col="red",main="densityofmpg案例1：年齡分…案例1：年齡分…共500個(gè)記reading,music,moviessports,musicmovies,R:2,C#:4,Python:3R:3,Java:2,C++:5R:1,C++:4,對(duì)于數(shù)據(jù)中同時(shí)使用R和Python各至少案例1：年齡分案例1：年齡分1&案例1：年齡分25965964413521221112案例1：年齡分259659644135212211121212234464754221119221462393331112案例2：案例2：GitHub案例2：GitHub案例2：GitHubHadley案例2：GitHub>Hadley案例2：GitHub>>案例2：GitHublist.sort(-案例2：GitHublist.sort(-##R26251C31313案例2：GitHub案例2：GitHub04040220307R311226011013Hadley的原創(chuàng)R案例2：GitHubHadley的原創(chuàng)R案例2：GitHublist.sort(-=RHadley的原創(chuàng)RHadley的原創(chuàng)R案例2：GitHubHadley的原創(chuàng)R案例2：GitHubHadley的原創(chuàng)R案例2：GitHublist.sort(-####案例案例2：GitHubrepos%>>%list.filter(any(grepl("plot|vis",c(name,list.sort(-stargazers_count)%>>%##"vis-dplayer的擴(kuò)展包有哪案例2：GitHubstringdistdplayer的擴(kuò)展包有哪案例2：GitHubstringdist=#…"data/"%>>%s=TRUE)list.filter((.)$size>0)list.map(read.csv(.,header=TRUE,stringsAsFactors=FALSE))%>>%…library(pipeR);library(rlist);"data/"list.files("\\.json",slibrary(pipeR);library(rlist);"data/"list.files("\\.json",s=TRUE)list.load(action=list.select(type,k1,k2,p=list.stack%>>%filter(p<=quantile(p,0.95)mutate(k3=k1+k2*q)lm(formula=p~k1+k2+q)feat