无法通过 CountryCode 将国家转换为大陆

如何解决无法通过 CountryCode 将国家转换为大陆

library(tidyverse)
library(readr)
library(countrycode)
library(stringr)

B07 <- read_csv("Downloads/BorderData/BorderApprehension2007.csv")
B08 <- read_csv("Downloads/BorderData/BorderApprehension2008.csv")

B07[is.na(B07)] = 0
B08[is.na(B08)] = 0
# and so on...
B07$CITIZENSHIP <- str_to_title(B07$CITIZENSHIP)

B07$continent <- countrycode(sourcevar = B07[,"CITIZENSHIP"],origin = "country.name",destination = "continent")

我想指定一个大陆而不是国家的名称，但我一直遇到这个错误...

国家代码错误(sourcevar = B07[,: sourcevar 必须是字符或数字向量。当用户传递tibble（例如，来自dplyr）时，通常会出现此错误而不是来自 data.frame 的列向量（即 my_tbl[,2] vs. my_df[,2] vs. my_tbl[2]）

这是我的数据图像：

解决方法

正如错误所说：“sourcevar 必须是字符或数字向量。当用户传递 tibble（例如，来自 dplyr）而不是来自 data.frame（即 my_tbl[,2 ] vs. my_df[,2] vs. my_tbl[[2]])"

看看 B07[,"CITIZENSHIP"] 与 B07[["CITIZENSHIP"]] 或 B07$CITIZENSHIP 的结果之间的差异

library(tibble)
library(countrycode)

B07 <- tibble(CITIZENSHIP = c("United States","Canada","Mexico"))

countrycode(sourcevar = B07[,"CITIZENSHIP"],origin = "country.name",destination = "continent")
#> Error in countrycode(sourcevar = B07[,: sourcevar must be a character or numeric vector. This error often
#>              arises when users pass a tibble (e.g.,from dplyr) instead of a
#>              column vector from a data.frame (i.e.,my_tbl[,2] vs. my_df[,2]
#>                                               vs. my_tbl[[2]])

countrycode(sourcevar = B07[["CITIZENSHIP"]],destination = "continent")
#> [1] "Americas" "Americas" "Americas"

countrycode(sourcevar = B07$CITIZENSHIP,destination = "continent")
#> [1] "Americas" "Americas" "Americas"


B07[,"CITIZENSHIP"]
#> # A tibble: 3 x 1
#>   CITIZENSHIP  
#>   <chr>        
#> 1 United States
#> 2 Canada       
#> 3 Mexico

B07[["CITIZENSHIP"]]
#> [1] "United States" "Canada"        "Mexico"

B07$CITIZENSHIP
#> [1] "United States" "Canada"        "Mexico"