使用googleway与ggmap的geocode函数处理邮政编码地理编码报错求助

问题：使用ggmap和googleway进行邮政编码地理编码时出错 #

一、ggmap代码及错误 #

library(ggmap)
library(tidyverse)
# 创建邮政编码数据框
data.new <- c(21022, 20380, 22194, 20414, 20402, 22350, 20451, 56998, 88888,
          20417, 75059, 90210, 11437, 10101, 10275, 10269, 10111, 98490)
data.new <- data.frame(data.new)
data.new <- data.new %>% rename(zipcode=data.new)
data.new$zipcode <- as.character(data.new$zipcode)
register_google(key = "api_key")
data.new_ggmap <- geocode(location = data.new$zipcode, output = "latlona", source = "google")
data.new_ggmap <- cbind(data.new, data.new_ggmap)

# 打印结果
data.new_ggmaps[, 1:18]

错误信息：

Warning: Geocoding "20380" failed with error:

二、googleway代码及错误 #

###OPTION2##############################################################
library(googleway)
library(tidyverse)
google_api_key <- "api_key"

# 创建邮政编码数据框
data.new <- c(21022, 20380, 22194, 20414, 20402, 22350, 20451, 56998, 88888,
              20417, 75059, 90210, 11437, 10101, 10275, 10269, 10111, 98490)
data.new <- data.frame(data.new)
data.new <- data.new %>% rename(zipcode=data.new)
data.new$zipcode <- as.character(data.new$zipcode)

# 初始化存储谷歌数据的列
data.new$goog_address_components_ <- NA
data.new$goog_formatted_address_ <- NA
data.new$goog_geometry_ <- NA
data.new$goog_place_id_ <- NA
data.new$goog_types_ <- NA
data.new$latitude <- NA
data.new$longitude <- NA

# 循环遍历数据框，将每个邮政编码传入谷歌API
for(k in 1:nrow(data.new)){
  
  # 打印循环索引查看进度
  print(k)
  
  # 使用tryCatch捕获错误，遇到问题时跳过当前项继续执行
  tryCatch({ 
    
    # 定义搜索字符串为当前邮政编码
    search_string <- data.new$zipcode[k]
    
    # 调用googleway的地理编码函数，需使用自己的谷歌API密钥
    response<- google_geocode(search_string,
                              key = google_api_key)
    
    # 从API响应中提取结果
    results_df <- response$results 
    
    # 将API响应结果添加到现有数据框
    data.new$goog_address_components_[k] <- results_df$address_components
    data.new$goog_formatted_address_[k] <- results_df$formatted_address
    data.new$goog_geometry_[k] <- results_df$geometry
    data.new$goog_place_id_[k] <- results_df$place_id
    data.new$goog_types_[k] <- results_df$types
    
    
  }, error = function(e){cat("ERROR :",conditionMessage(e), "\n")})
  
}

#########################################################################

错误信息：

[1] 1
[1] 2
ERROR : replacement has 17 rows, data has 18 
[1] 3
ERROR : replacement has 17 rows, data has 18 
[1] 4
ERROR : replacement has 17 rows, data has 18 
[1] 5
ERROR : replacement has 17 rows, data has 18 
[1] 6
ERROR : replacement has 17 rows, data has 18 
[1] 7
ERROR : replacement has 17 rows, data has 18 
[1] 8
ERROR : replacement has 17 rows, data has 18 
[1] 9
ERROR : replacement has 17 rows, data has 18 
[1] 10
ERROR : replacement has 17 rows, data has 18 
[1] 11
ERROR : replacement has 17 rows, data has 18 
[1] 12
ERROR : replacement has 17 rows, data has 18 
[1] 13
ERROR : replacement has 17 rows, data has 18 
[1] 14
ERROR : replacement has 17 rows, data has 18 
[1] 15
ERROR : replacement has 17 rows, data has 18 
[1] 16
ERROR : replacement has 17 rows, data has 18 
[1] 17
ERROR : replacement has 17 rows, data has 18 
[1] 18
ERROR : replacement has 17 rows, data has 18 
Warning message:
In data.new$goog_geometry_[k] <- results_df$geometry :
  number of items to replace is not a multiple of replacement length

修复方案 #

针对googleway的错误修复

错误根源是response$results中的address_components、geometry等字段是嵌套列表结构，直接赋值给数据框的普通列会导致长度不匹配。只需提取实际需要的字段（比如经纬度）即可解决：

library(googleway)
library(tidyverse)
google_api_key <- "你的谷歌API密钥"

# 创建邮政编码数据框
data.new <- tibble(zipcode = as.character(c(21022, 20380, 22194, 20414, 20402, 22350, 20451, 56998, 88888,
          20417, 75059, 90210, 11437, 10101, 10275, 10269, 10111, 98490)))

# 循环处理每个邮政编码，提取关键信息
for(k in 1:nrow(data.new)){
  print(k)
  tryCatch({ 
    search_string <- data.new$zipcode[k]
    response <- google_geocode(search_string, key = google_api_key)
    
    # 仅当API返回有效结果时提取数据
    if(nrow(response$results) > 0){
      data.new$latitude[k] <- response$results$geometry$location$lat
      data.new$longitude[k] <- response$results$geometry$location$lng
      data.new$formatted_address[k] <- response$results$formatted_address
      data.new$place_id[k] <- response$results$place_id
    }
    
  }, error = function(e){cat("ERROR :",conditionMessage(e), "\n")})
}

# 查看最终结果
print(data.new)

针对ggmap的错误修复

常见错误原因包括：API密钥未启用地理编码服务、无效邮政编码、API配额不足或权限限制。修复步骤如下：

1. 登录谷歌云控制台，确保「地理编码API」已启用；
2. 检查API密钥权限，允许当前家用IP访问（可临时设置为不限IP，注意密钥安全）；
3. 过滤无效邮编（比如88888是虚构邮编），或在编码时处理失败项；

修改后的ggmap代码：

library(ggmap)
library(tidyverse)
register_google(key = "你的谷歌API密钥")

data.new <- tibble(zipcode = as.character(c(21022, 20380, 22194, 20414, 20402, 22350, 20451, 56998, 88888,
          20417, 75059, 90210, 11437, 10101, 10275, 10269, 10111, 98490)))

# 批量地理编码，自动处理失败项
data.new_ggmap <- data.new %>%
  mutate(geo_result = map(zipcode, ~{
    tryCatch(geocode(location = ., output = "latlona", source = "google"),
             error = function(e) tibble(lat=NA, lon=NA, address=NA, type=NA))
  })) %>%
  unnest(geo_result)

# 查看结果
print(data.new_ggmap)

内容的提问来源于stack exchange，提问作者Kenny