Reverse the order of input to the series of dplyr::*_join examples using data from the Nobel laureates in literature and explain the resulting output.
dta1 <- read.table("C:/Users/TheorEco Lab/Desktop/108-2/DataManagement/0330/nobel_countries.txt", header=T)
dta2 <- read.table("C:/Users/TheorEco Lab/Desktop/108-2/DataManagement/0330/nobel_winners.txt", header=T)str(dta1)
#> 'data.frame': 8 obs. of 2 variables:
#> $ Country: Factor w/ 7 levels "Canada","China",..: 3 6 6 7 1 2 4 5
#> $ Year : int 2014 1950 2017 2016 2013 2012 2015 2011
str(dta2)
#> 'data.frame': 7 obs. of 3 variables:
#> $ Name : Factor w/ 7 levels "Alice Munro",..: 6 2 4 3 1 5 7
#> $ Gender: Factor w/ 2 levels "Female","Male": 2 2 2 2 1 2 1
#> $ Year : int 2014 1950 2017 2016 2013 2012 1938dplyr::inner_join(dta1, dta2)
#> Joining, by = "Year"
#> Country Year Name Gender
#> 1 France 2014 Patrick Modiano Male
#> 2 UK 1950 Bertrand Russell Male
#> 3 UK 2017 Kazuo Ishiguro Male
#> 4 US 2016 Bob Dylan Male
#> 5 Canada 2013 Alice Munro Female
#> 6 China 2012 Mo Yan Male兩筆資料根據其年份合併並顯示年份有所交集的 6 筆觀察值，兩個資料的所有欄位皆有顯示。
dplyr::semi_join(dta1, dta2)
#> Joining, by = "Year"
#> Country Year
#> 1 France 2014
#> 2 UK 1950
#> 3 UK 2017
#> 4 US 2016
#> 5 Canada 2013
#> 6 China 2012根據年份合併，一樣只顯示有交集的年份資料，但只顯示 dta1 有的欄位。
dplyr::left_join(dta1, dta2)
#> Joining, by = "Year"
#> Country Year Name Gender
#> 1 France 2014 Patrick Modiano Male
#> 2 UK 1950 Bertrand Russell Male
#> 3 UK 2017 Kazuo Ishiguro Male
#> 4 US 2016 Bob Dylan Male
#> 5 Canada 2013 Alice Munro Female
#> 6 China 2012 Mo Yan Male
#> 7 Russia 2015 <NA> <NA>
#> 8 Sweden 2011 <NA> <NA>所有 dta1 的國家都有呈現，也就是呈現其 row，欄位則是同時呈現 dta1 和 dta2 的聯集。
dplyr::anti_join(dta1, dta2)
#> Joining, by = "Year"
#> Country Year
#> 1 Russia 2015
#> 2 Sweden 2011顯示 dta1 的欄位資料，但只顯示只有 dta1 有但 dta2 沒有的觀察值。
dplyr::full_join(dta1, dta2)
#> Joining, by = "Year"
#> Country Year Name Gender
#> 1 France 2014 Patrick Modiano Male
#> 2 UK 1950 Bertrand Russell Male
#> 3 UK 2017 Kazuo Ishiguro Male
#> 4 US 2016 Bob Dylan Male
#> 5 Canada 2013 Alice Munro Female
#> 6 China 2012 Mo Yan Male
#> 7 Russia 2015 <NA> <NA>
#> 8 Sweden 2011 <NA> <NA>
#> 9 <NA> 1938 Pearl Buck Female顯示完全 dta1 和 dta2 的聯集，所有的欄與行皆呈現，年份重複的則合併，無法合併的則有遺漏值。