在 rworldmap 中查看 joinCountryData2Map 的不匹配国家？

Question

我正在使用 rworldmap 中的 joinCountryData2Map 函数将我的数据与世界地图上的国家相匹配。

我得到这个结果：

230 codes from your data successfully matched countries in the map
11 codes from your data failed to match with a country code in the map
11 codes from the map weren't represented in your data

我不知道如何查看这两个包含 11 个国家/地区的列表。我猜测这 11 个国家/地区的 ISO2 代码存在问题，我需要更正这些代码，但我不确定在无法查看这两个列表的情况下检查哪些。

我猜想有一个解决方案只是 View(SomeObject$Countries)，但我没能找到任何有效的方法。

Answer 1

设置joinCountryData2Map(...,verbose=TRUE)在控制台打印匹配失败的国家名称。

From the FAQ: "您可以看到成功加入的国家/地区的摘要输出到控制台。您可以指定 verbose=TRUE 以获取完整的国家/地区列表"

library(rworldmap)

data(countryExData)

# Set Angola to fail
countryExData[countryExData$ISO3V10 == "AGO", "ISO3V10"] <- "AGO_FAIL"

# Attempt to join
# With verbose=TRUE, failed joins (ie Angola) are printed in the console
sPDF <- joinCountryData2Map(
  countryExData[,c("ISO3V10", "Country")],
  joinCode = "ISO3",
  nameJoinColumn = "ISO3V10",
  verbose = TRUE)

# > 148 codes from your data successfully matched countries in the map
# > 1 codes from your data failed to match with a country code in the map
# >      failedCodes failedCountries
# > [1,] "AGO_FAIL"  "Angola"       
# > 95 codes from the map weren't represented in your data

但是，如果您想以编程方式获取有关失败连接的信息怎么办？我可能错过了一些东西，但我没有看到相应的选项（即 str(sPDF) 或函数参数）。但是，查看 joinCountryData2Map() 的内部结构，对象 failedCountries 包含您想要的信息，因此将它包含在 returned 对象中应该很容易。

以下是将包含两个元素的列表 joinCountryData2Map() 修改为 return 的方法：第一个元素是默认对象，第二个元素是 failedCountries.

# Modify the function to return the failed joins in the environment
joinCountryData2Map_wfails <- function(
  dF, joinCode = "ISO3", nameJoinColumn = "ISO3V10",
  nameCountryColumn = "Country", suggestForFailedCodes = FALSE, 
  mapResolution = "coarse", projection = NA, verbose = FALSE) {
  
  # Retain successful join as first element and failed join as second element
  ll <- list() # MODIFIED
  mapWithData <- getMap(resolution = mapResolution)
  if (!is.na(projection)) 
    warning("the projection argument has been deprecated, returning Lat Lon, use spTransform from package rgdal as shown in help details or the FAQ")
  listJoinCodesNew <- c("ISO_A2", "ISO_A3", "FIPS_10_", 
                        "ADMIN", "ISO_N3")
  listJoinCodesOld <- c("ISO2", "ISO3", "FIPS", 
                        "NAME", "UN")
  listJoinCodes <- c(listJoinCodesOld, listJoinCodesNew)
  if (joinCode %in% listJoinCodes == FALSE) {
    stop("your joinCode (", joinCode, ") in joinCountryData2Map() is not one of those supported. Options are :", 
         paste(listJoinCodes, ""), "\n")
    return(FALSE)
  }
  joinCodeOld <- joinCode
  if (joinCode %in% listJoinCodesOld) {
    joinCode <- listJoinCodesNew[match(joinCode, listJoinCodesOld)]
  }
  if (is.na(match(nameJoinColumn, names(dF)))) {
    stop("your chosen nameJoinColumn :'", nameJoinColumn, 
         "' seems not to exist in your data, columns = ", 
         paste(names(dF), ""))
    return(FALSE)
  }
  dF[[joinCode]] <- as.character(dF[[nameJoinColumn]])
  dF[[joinCode]] <- gsub("[[:space:]]*$", "", dF[[joinCode]])
  if (joinCode == "ADMIN") {
    dF$ISO3 <- NA
    for (i in 1:nrow(dF)) dF$ISO3[i] = rwmGetISO3(dF[[joinCode]][i])
    joinCode = "ISO3"
    nameCountryColumn = nameJoinColumn
  }
  matchPosnsInLookup <- match(as.character(dF[[joinCode]]), 
                              as.character(mapWithData@data[[joinCode]]))
  failedCodes <- dF[[joinCode]][is.na(matchPosnsInLookup)]
  numFailedCodes <- length(failedCodes)
  numMatchedCountries <- nrow(dF) - numFailedCodes
  cat(numMatchedCountries, "codes from your data successfully matched countries in the map\n")
  failedCountries <- dF[[nameCountryColumn]][is.na(matchPosnsInLookup)]
  failedCountries <- cbind(failedCodes, failedCountries = as.character(failedCountries))
  cat(numFailedCodes, "codes from your data failed to match with a country code in the map\n")
  if (verbose) 
    print(failedCountries)
  matchPosnsInUserData <- match(as.character(mapWithData@data[[joinCode]]), 
                                as.character(dF[[joinCode]]))
  codesMissingFromUserData <- as.character(mapWithData@data[[joinCode]][is.na(matchPosnsInUserData)])
  countriesMissingFromUserData <- as.character(mapWithData@data[["NAME"]][is.na(matchPosnsInUserData)])
  numMissingCodes <- length(codesMissingFromUserData)
  cat(numMissingCodes, "codes from the map weren't represented in your data\n")
  mapWithData@data <- cbind(mapWithData@data, dF[matchPosnsInUserData, 
  ])
  invisible(mapWithData)
  
  ll[[1]] <- mapWithData # MODIFIED
  ll[[2]] <- failedCountries # MODIFIED
  return(ll) # MODIFIED
}

用法：

sPDF_wfails <- joinCountryData2Map_wfails(
  countryExData[,c("ISO3V10", "Country")],
  joinCode = "ISO3",
  nameJoinColumn = "ISO3V10",
  verbose = TRUE)

# This is the result of the original function
# sPDF_wfails[[1]]

# This is info on the failed joins
sPDF_wfails[[2]]

# >     failedCodes failedCountries
# > [1,] "AGO_FAIL"  "Angola"

在 rworldmap 中查看 joinCountryData2Map 的不匹配国家？

See unmatched countries for joinCountryData2Map in rworldmap?

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