R：仅从街道名称，城市和州获得邮政编码

Question

我有一个数据集，其中包含与不同城市和州的房地产相关的信息。当前看起来像这样：

Id| StreetName               | City         | State
=================================================
1 | 100 Railroad Ave         | Elkton       | MD
2 | 414 Grant St             | Pittsburgh   | PA
3 | 1400 John F Kennedy Blvd | Philadelphia | PA
4 | 800 N French St          | Wilmington   | DE

r中是否有一个可用于获取每行邮政编码的软件包？我想根据邮政编码创建一个密度图。我当前的数据包括数千行。

Answer 1

有可能，但需要美国邮政服务提供的（免费）帐户。

使用rusps软件包（更多信息：https://github.com/hansthompson/rusps）

输出有些重复，该函数似乎不是可传递的，但在您发布的数据上效果很好。清理％join到您的数据（或单独使用）应该不太困难。

addresses <- tibble::tribble(
  ~Id,                ~StreetName,          ~City, ~State,
    1,         "100 Railroad Ave",       "Elkton",   "MD",
    2,             "414 Grant St",   "Pittsburgh",   "PA",
    3, "1400 John F Kennedy Blvd", "Philadelphia",   "PA",
    4,          "800 N French St",   "Wilmington",   "DE"
  )

# devtools::install_github('hansthompson/rusps')
library(rusps)
library(XML)
username <- 'XXXYYYYYZZZZ' # get this quickly and freely 
                           #by signing up at https://registration.shippingapis.com/ (not commercial).

output <- validate_address_usps(street = addresses$StreetName, 
                                city = addresses$City, 
                                state = addresses$State, 
                                username = username)

output

                   Address2         City State  Zip5 Zip4 .attrs
1          100 RAILROAD AVE       ELKTON    MD 21921 5537      0
2              414 GRANT ST   PITTSBURGH    PA 15219 2409      1
3  1400 JOHN F KENNEDY BLVD PHILADELPHIA    PA 19107 3200      2
4           800 N FRENCH ST   WILMINGTON    DE 19801 3594      3
5                        NA           NA    NA    NA   NA      0
6          100 RAILROAD AVE       ELKTON    MD 21921 5537      0
7              414 GRANT ST   PITTSBURGH    PA 15219 2409      0
8  1400 JOHN F KENNEDY BLVD PHILADELPHIA    PA 19107 3200      0
9          100 RAILROAD AVE       ELKTON    MD 21921 5537      1
10             414 GRANT ST   PITTSBURGH    PA 15219 2409      1
11         100 RAILROAD AVE       ELKTON    MD 21921 5537      0
12             414 GRANT ST   PITTSBURGH    PA 15219 2409      0
13 1400 JOHN F KENNEDY BLVD PHILADELPHIA    PA 19107 3200      0
14          800 N FRENCH ST   WILMINGTON    DE 19801 3594      0

出于某种原因，所有返回的列都是列表列。清理：

unnest(output, cols = everything()) %>% 
    group_by(Address2) %>% 
    slice(1)

# A tibble: 5 x 6
# Groups:   Address2 [5]
  Address2                 City         State Zip5  Zip4  .attrs
  <chr>                    <chr>        <chr> <chr> <chr> <chr> 
1 100 RAILROAD AVE         ELKTON       MD    21921 5537  0     
2 1400 JOHN F KENNEDY BLVD PHILADELPHIA PA    19107 3200  2     
3 414 GRANT ST             PITTSBURGH   PA    15219 2409  1     
4 800 N FRENCH ST          WILMINGTON   DE    19801 3594  3     
5 NA                       NA           NA    NA    NA    0