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1 Excel GDP Excel Excel GDP 10 7 CSV CSV Stata
2 5 1 Excel, CSV, Stata JSON, XML R 2 Excel : Microsoft Excel.xls.xlsx CSV : Comma Separated Values Stata : Stata JSON: JavaScript JavaScript XML: XML Extensible Markup Language Web HTML Hyper Text Markup Language XML R Excel CSV Stata 3 3 Excel 3.1 GDP GDP R (1) = II 2
3 3.2 Excel 5 (2) SNA SNA (3) IV. 1 27ffm1rn jp.xls 3.2 Excel R R readxl Excel II 3
4 3.3 Excel 5 readxl > install.packages("readxl") readxl > library(readxl) Excel read_excel() > help(read_excel) 3.3 Excel Excel Excel 3 read_excel() 1 1 read_excel() Excel > gdp <- read_excel(".xls") # R R working directory R getwd() > getwd() # [1] "/Users/shito/Documents/git-repositories/R-programming-lecnote/handout" setwd() > setwd("/users/shito") # /Users/shito Mac Windows E seminer > setwd("e:/seminer") II 4
5 3.3 Excel 5 27ffm1rn jp.xls Windows E > gdp <- read_excel("e:/ /27ffm1rn_jp.xls") # Windows E 27ffm1rn jp.xls data > gdp <- read_excel("data/27ffm1rn_jp.xls") Excel skip=6 1 col_names TRUE col_names TRUE > gdp <- read_excel("data/27ffm1rn_jp.xls", skip=6, col_names=true) > dim(gdp) # [1] gdp > gdp[1:3, 1:4] # A tibble: 3 x 4 X 1 `1994` `1995` `1996` <chr> <dbl> <dbl> <dbl> A tibble: 3 x 4 gdp Tibble Tibble > is.data.frame(gdp) # [1] TRUE > gdp <- as.data.frame(gdp) # as. Excel R II 5
6 > rownames(gdp) <- gdp[, 1] # <-- row.names b Excel 1 Excel NA read_excel() trim=true GDP > gdp[,1] # Excel NA NA > gdp <- gdp[!is.na(gdp[,1]),] # NA > dim(gdp) # [1] II 6
7 3.4 5 Excel 3 gdp 2 NA 3 > gdp <- gdp[1:(dim(gdp)[1]-3), ] # 3 > dim(gdp) # [1] :(dim(gdp)[1]-3) > 1:dim(gdp)[1]-3 # (1:dim(gdp)[1]) - 3 [1] [28] > 1:(dim(gdp)[1]-3) # [1] [28] gsub() global substitution gsub(" ", " ", ) > cn <- gsub(" ", "", gdp[, 1]) # > cn[1:7] # [1] " " [2] " " [3] " " [4] " " [5] " ) " [6] " " [7] " " > cn <- gsub(" ", "", cn) # cn gdp duplicated() TRUE duplicated() TRUE > n <- 1:10 # 1 10 > n[c(5, 10)] <- 1 # > n [1] II 7
8 3.4 5 > duplicated(n) # 5 10 TRUE [1] FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE TRUE > n[duplicated(n)] # 2 [1] 1 1 duplicated() cn > cn[duplicated(cn)] [1] " " " " " " " " Excel cn > gdp <- gdp[cn!=" ", ] > cn <- cn[cn!=" "] > dim(gdp) # 2 55 [1] > (1:length(cn))[duplicated(cn)] # [1] > n <- (1:length(cn))[duplicated(cn)][1:2] # 2 > cn[n] # [1] " " " " > cn[n]<- paste(cn[n], " ", sep="") # paste > cn[n] # [1] " " " " Excel cn gdp > colnames(gdp) [1] "1994" "1995" "1996" "1997" "1998" "1999" "2000" "2001" "2002" "2003" "2004" [12] "2005" "2006" "2007" "2008" "2009" "2010" "2011" "2012" "2013" "2014" "2015" II 8
9 3.4 5 $ 1994 > gdp$1994 # < > gdp$"1994" Y R > paste("y", colnames(gdp), sep="") # [1] "Y1994" "Y1995" "Y1996" "Y1997" "Y1998" "Y1999" "Y2000" "Y2001" "Y2002" "Y2003" [11] "Y2004" "Y2005" "Y2006" "Y2007" "Y2008" "Y2009" "Y2010" "Y2011" "Y2012" "Y2013" [21] "Y2014" "Y2015" > colnames(gdp) <- paste("y", colnames(gdp), sep="") > gdp$y1994 # $ [1] [10] [19] [28] [37] NA [46] NA NA NA > rownames(gdp)[is.na(gdp$y1994)] # NA [1] "" > gdp <- gdp[rownames(gdp)!= "", ] # gdp > gdp$y1994 [1] [10] [19] [28] [37] [46] Excel 3 4 > gdp[1:3, 1:4] Y1994 Y1995 Y1996 Y II 9
10 5 4 R ls() > ls() # list [1] "cn" "gdp" "n" save() load().rdata > save(gdp, file="ch05-gdp.rdata") # gdp ch05-gdp.rdata > save(gdp, cn, file="ch05-gdp.rdata") # gdp cn 5 load() gdp cn rm() remove > rm(gdp, cn) # gdp cn remove > ls() # gdp cn [1] "n" load() > load("ch05-gdp.rdata") > ls() [1] "cn" "gdp" "n" > gdp[1:3, 1:4] Y1994 Y1995 Y1996 Y II 10
11 5 6 GDP R GDP GDP GDI GDE > rownames(gdp)[c(37, 40)] [1] " " " " 2015 > gdp[c(" ", " "), "Y2015"] [1] Excel 3 GDE GDP GDP > max(gdp[" ",]) # GDP [1] > min(gdp[" ",]) # GDP [1] Excel GDP GDP GDP y > y <- gdp[" ",] > colnames(gdp)[y == max(y)] # y y [1] "Y2015" > colnames(gdp)[y == min(y)] # y y [1] "Y1994" GDP GDP 1 I II 11
12 5 > plot(1994:2015, y, type="l", xlab="year", ylab="gdp") GDP Year plot() plot(x, y) x y x :2015 y GDP y 2 type="l" line xlab ylab x y GDP 4 GDP CSV CSV Comma Separated Values CSV CSV 5 II 12
13 (1) URL (2) (3) ippan 2009zensho 2 csv PDF ippan_2009zensho_z_dataset.csv 7.2 CSV CSV read.csv() > help(read.csv) Usage ippan_2009zensho_z_dataset.csv skip=5 header=true Excel Shift JIS R UTF8 encoding="shift_jis" > microdata <- read.csv("data/ippan_2009zensho_z_dataset.csv", # + skip=5, header=true, encoding="shift_jis") II 13
14 5 > dim(microdata) # [1] head() tail() > head(microdata) # > tail(microdata) # RData > save(microdata, file="microdata.rdata") # 8 Stata Stata Stata.dta Stata Stata R Stata read.dta() foreign > library(foreign) > library(help=foreign) # foreign > help(read.dta) # read.dta Stata read.dta() > stata.data <- read.dta(".dta") # Stata dta 9 GDP GDP R GDP GDP GDP 10 II 14
15 5 10 GDP Purchasing Power Parity Rate PPP PPP GDP GDP GDP GDP GDP per capita (1) World Bank GDP ppp per capita (2) Download CSV (3) API NY API_NY.GDP.PCAP.PP.CD_DS2_en_csv_v2.csv R ppp (4) (5) ppp 1 1 (6) Indicator.Name Indicator.Code (7) 2015 GDP (8) GDP GDP (9) ppp WorldBank_GDP.RData (10) ppp II 15
16 5 (11) WorldBank_GDP.RData ppp II 16
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