R：不可能完成的任务？如何将 "New York" 分配给一个县

Question

我运行遇到将县分配给某些城市的问题。通过 acs 包查询时

> geo.lookup(state = "NY", place = "New York")
  state state.name                                                                 county.name place             place.name
1    36   New York                                                                        <NA>    NA                   <NA>
2    36   New York Bronx County, Kings County, New York County, Queens County, Richmond County 51000          New York city
3    36   New York                                                               Oneida County 51011 New York Mills village

，你可以看到，比如“纽约”，有一堆县。洛杉矶、波特兰、俄克拉荷马州、哥伦布等也是如此。这样的数据怎么能分配给一个“县”？

以下代码当前用于将“county.name”与相应的县 FIPS 代码匹配。不幸的是，它只适用于查询中只输出一个县名的情况。

脚本

dat <- c("New York, NY","Boston, MA","Los Angeles, CA","Dallas, TX","Palo Alto, CA")
dat <- strsplit(dat, ",")
dat

library(tigris)
library(acs)
data(fips_codes) # FIPS codes with state, code, county information

GeoLookup <- lapply(dat,function(x) {
  geo.lookup(state = trimws(x[2]), place = trimws(x[1]))[2,]
})

df <- bind_rows(GeoLookup)

#Rename cols to match
colnames(fips_codes) = c("state.abb", "statefips", "state.name", "countyfips", "county.name")

# Here is a problem, because it works with one item in "county.name" but not more than one (see output below).

df <- df %>% left_join(fips_codes, by = c("state.name", "county.name"))
df

Returns:

  state    state.name                                                                  county.name place           place.name state.abb statefips countyfips
1    36      New York  Bronx County, Kings County, New York County, Queens County, Richmond County 51000        New York city      <NA>      <NA>       <NA>
2    25 Massachusetts                                                               Suffolk County  7000          Boston city        MA        25        025
3     6    California                                                           Los Angeles County 20802 East Los Angeles CDP        CA        06        037
4    48         Texas Collin County, Dallas County, Denton County, Kaufman County, Rockwall County 19000          Dallas city      <NA>      <NA>       <NA>
5     6    California                                                             San Mateo County 20956  East Palo Alto city        CA        06        081

为了保留数据，left_join 最好匹配为“查找包含 place.name（没有在名称中附加 xy city），或者默认选择第一项。很高兴看到如何做到这一点。

总的来说：我想，没有比这种方法更好的方法了吗？

感谢您的帮助！

Answer 1

像下面这样的代码如何创建一个 "long" 数据框用于加入。我们使用 tidyverse 管道运算符来链接操作。 strsplit returns 一个列表，我们 unnest 将列表值（与 state.name 和 place.name 的每个组合对应的县名）堆叠成一个长每个 county.name 现在都有自己的行的数据框。

library(tigris)
library(acs)  
library(tidyverse)

dat = geo.lookup(state = "NY", place = "New York")

  state state.name                                                                 county.name place             place.name
1    36   New York                                                                        <NA>    NA                   <NA>
2    36   New York Bronx County, Kings County, New York County, Queens County, Richmond County 51000          New York city
3    36   New York                                                               Oneida County 51011 New York Mills village

dat = dat %>% 
  group_by(state.name, place.name) %>% 
  mutate(county.name = strsplit(county.name, ", ")) %>% 
  unnest

  state state.name place             place.name     county.name
  <chr>      <chr> <int>                  <chr>           <chr>
1    36   New York    NA                   <NA>            <NA>
2    36   New York 51000          New York city    Bronx County
3    36   New York 51000          New York city    Kings County
4    36   New York 51000          New York city New York County
5    36   New York 51000          New York city   Queens County
6    36   New York 51000          New York city Richmond County
7    36   New York 51011 New York Mills village   Oneida County

更新：关于你评论中的第二个问题，假设你已经有了都市区的向量，那么这个怎么样：

dat <- c("New York, NY","Boston, MA","Los Angeles, CA","Dallas, TX","Palo Alto, CA")

df <- map_df(strsplit(dat, ", "), function(x) {
  geo.lookup(state = x[2], place = x[1])[-1, ] %>% 
    group_by(state.name, place.name) %>%
    mutate(county.name = strsplit(county.name, ", ")) %>%
    unnest
})

df

   state    state.name place             place.name        county.name
 1    36      New York 51000          New York city       Bronx County
 2    36      New York 51000          New York city       Kings County
 3    36      New York 51000          New York city    New York County
 4    36      New York 51000          New York city      Queens County
 5    36      New York 51000          New York city    Richmond County
 6    36      New York 51011 New York Mills village      Oneida County
 7    25 Massachusetts  7000            Boston city     Suffolk County
 8    25 Massachusetts  7000            Boston city     Suffolk County
 9     6    California 20802   East Los Angeles CDP Los Angeles County
10     6    California 39612   Lake Los Angeles CDP Los Angeles County
11     6    California 44000       Los Angeles city Los Angeles County
12    48         Texas 19000            Dallas city      Collin County
13    48         Texas 19000            Dallas city      Dallas County
14    48         Texas 19000            Dallas city      Denton County
15    48         Texas 19000            Dallas city     Kaufman County
16    48         Texas 19000            Dallas city    Rockwall County
17    48         Texas 40516       Lake Dallas city      Denton County
18     6    California 20956    East Palo Alto city   San Mateo County
19     6    California 55282         Palo Alto city Santa Clara County

更新 2： 如果我理解您的意见，对于具有多个县的城市（实际上是示例中的地名），我们只需要包含相同名称的县作为城市（例如，纽约市的纽约县），否则列表中的第一个县。以下代码选择一个与城市同名的县，如果没有，则选择该城市的第一个县。您可能需要稍微调整一下以使其适用于整个 U.S。例如，要使其适用于路易斯安那州，您可能需要 gsub(" County| Parish"... 而不是 gsub(" County"....

map_df(strsplit(dat, ", "), function(x) {
  geo.lookup(state = x[2], place = x[1])[-1, ] %>% 
    group_by(state.name, place.name) %>%
    mutate(county.name = strsplit(county.name, ", ")) %>%
    unnest %>% 
    slice(max(1, which(grepl(sub(" [A-Za-z]*$","", place.name), gsub(" County", "", county.name))), na.rm=TRUE))
})

   state    state.name place             place.name        county.name
   <chr>         <chr> <int>                  <chr>              <chr>
 1    36      New York 51000          New York city    New York County
 2    36      New York 51011 New York Mills village      Oneida County
 3    25 Massachusetts  7000            Boston city     Suffolk County
 4     6    California 20802   East Los Angeles CDP Los Angeles County
 5     6    California 39612   Lake Los Angeles CDP Los Angeles County
 6     6    California 44000       Los Angeles city Los Angeles County
 7    48         Texas 19000            Dallas city      Dallas County
 8    48         Texas 40516       Lake Dallas city      Denton County
 9     6    California 20956    East Palo Alto city   San Mateo County
10     6    California 55282         Palo Alto city Santa Clara County

Answer 2

你能用类似下面的代码来准备数据吗？

new_york_data <- geo.lookup(state = "NY", place = "New York")

prep_data <- function(full_data){
  output <- data.frame()
  for(row in 1:nrow(full_data)){
    new_rows <- replicateCounty(full_data[row, ])
    output <- plyr::rbind.fill(output, new_rows)
  }
  return(output)
}


replicateCounty <- function(row){
  counties <- str_trim(unlist(str_split(row$county.name, ",")))

  output <- data.frame(state = row$state,
                       state.name = row$state.name,
                       county.name = counties,
                       place = row$place,
                       place.name = row$place.name)

  return(output)
}

prep_data(new_york_data)

有点乱，您需要 plyr 和 stringr 包。准备好数据后，您应该可以加入其中

R：不可能完成的任务？如何将 "New York" 分配给一个县

R: Mission impossible? How to assign "New York" to a county

r

dplyr

match

geocoding

acs

脚本