學習筆記，僅供參考
學習書目：《R語言空間數(shù)據(jù)處理與分析實踐教程》–盧賓賓;

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基礎數(shù)據(jù)操作與處理

設置工作路徑,并導入包

workL = "F:/MyStudio/Rstudio/RSpaceMetrology/myRdoc" setwd(workL) #getwd()

函數(shù)學習記錄表

數(shù)據(jù)類型轉(zhuǎn)換

a <- as("123", "numeric") b <- as.numeric("456") class(a) class(b)

match函數(shù)

test1 <- c("A", "A", "B", "B", "B") type_test1 <- unique(test1) print(type_test1) idx <- match(test1, type_test1) print(idx)

which.min和which.max

test2 <- c(9, 4, 7, 2, 9, 5, 3) which.min(test2) which.max(test2)

rev函數(shù)

rev函數(shù)可以實現(xiàn)向量或矩陣的翻轉(zhuǎn)；當進行矩陣的翻轉(zhuǎn)時,rev函數(shù)將矩陣當做一個向量處理，矩陣轉(zhuǎn)換為向量的原則以列優(yōu)先

test3 <- c(1:5) print(test3) print(rev(test3)) print("----------------------") test4 <- matrix(1:12, nrow = 3) print(test4) print(rev(test4)) print(matrix(rev(test4), nrow = 3))

用dplyr包中對數(shù)據(jù)進行處理

library(dplyr)data01 <- read.csv("comp.csv") head(data01) #選取Demo列 select(data01, "Dame") %>% head() #選取首字母以B開頭的列 filter(data01, Dame == 0) %>% head() #按照Dame列的大小給data01排序 arrange(data01, Dame) %>% head() #按照Dame列的大小對data01進行降序排序 arrange(data01, desc(Dame)) %>% head()

用rlist包處理關系型數(shù)據(jù)

library(rlist)#創(chuàng)建一個listperson <- list(p1=list(name="Ken",age=24,interest=c("reading","music","movies"),lang=list(r=2,csharp=4,python=3)),p2=list(name="James",age=25,interest=c("sports","music"),lang=list(r=3,java=2,cpp=5)),p3=list(name="Penny",age=24,interest=c("movies","reading"),lang=list(r=1,cpp=4,python=2)))str(person) list.map(person, age) list.map(person, names(lang)) p.age25 <- list.filter(person, age >= 25) str(p.age25) p.py3 <- list.filter(person, lang$python >= 3) str(p.py3)

利用lubridate包處理時間數(shù)據(jù)

library(lubridate)dateString <- c('20131113','120315','12/17/1996','09-01-01') (date <- parse_date_time(dateString, order = c('ymd','mdy','dmy','ymd'))) wday(date[1]) wday(date, label = TRUE) month(date)#查看是否有時間的交疊 begin1 <- ymd_hms("20150903, 12:00:00") end1 <- ymd_hms("20160804, 12:30:00") begin2 <- ymd_hms("20151203, 12:00:00") end2 <- ymd_hms("20160904, 12:30:00") (date_1 <- interval(begin1, end1)) (date_2 <- interval(begin2, end2)) int_overlaps(date_1, date_2)

利用tidyr包進行數(shù)據(jù)處理

library(tidyr)widedata <- data.frame(person=c('Alex','Bob','Cathy'),grade=c(2,3,4),score=c(78,89,88),age=c(18,19,18)) widedata #整合為長數(shù)據(jù) longdata <- gather(widedata, variable, value,-person) longdata#合并 wideunite<-unite(widedata, information, person, grade, score, age, sep= "-") wideunite #拆分 widesep <- separate(wideunite, information,c("person","grade","score","age"), sep = "-") widesep

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