add query column to `geocode()` result? #9

dpprdan · 2019-11-07T13:02:06Z

Potential use case: When geocoding, I would like to bind a source data frame to the results sf object. I.e. in the following example I would like to have the company name in the sf object.

library(hereR)

x <- data.frame(
  company = c("Schweizerische Bundesbahnen SBB", "Deutsche Bahn AG"),
  address = c("Wylerstrasse 123, 3000 Bern 65", "Potsdamer Platz 2, 10785 Berlin"),
  stringsAsFactors = FALSE
)

geocode(x$address)
#> Simple feature collection with 2 features and 10 fields
#> geometry type:  POINT
#> dimension:      XY
#> bbox:           xmin: 7.44657 ymin: 46.96138 xmax: 13.37525 ymax: 52.51005
#> epsg (SRID):    4326
#> proj4string:    +proj=longlat +datum=WGS84 +no_defs
#>                                        address          street houseNumber
#> 1    Wylerstrasse 123, 3014 Bern Bern, Schweiz    Wylerstrasse         123
#> 2 Potsdamer Platz 2, 10785 Berlin, Deutschland Potsdamer Platz           2
#>   postalCode   district   city          county  state country  type
#> 1       3014      Wyler   Bern Bern-Mittelland     BE     CHE point
#> 2      10785 Tiergarten Berlin          Berlin Berlin     DEU point
#>                    geometry
#> 1  POINT (7.44657 46.96138)
#> 2 POINT (13.37525 52.51005)

However, I don’t have an identical column in both data frames with which I could merge both. How would I be able do that? (In this simple example it would be possible to rbind() both objects, but that rests on the (fragile) assumption that both objects have the same nrow()).

One possible solution would be to add the query vector as a column to the results object.

munterfinger · 2019-11-09T23:56:44Z

geocode() now returns an sf object with row names that match the index of the geocoded addresses.

library(hereR)
library(sf)
#> Linking to GEOS 3.7.2, GDAL 2.4.2, PROJ 5.2.0

x <- data.frame(
  company = c("Schweizerische Bundesbahnen SBB", "Bahnhof AG", "Deutsche Bahn AG"),
  address = c("Wylerstrasse 123, 3000 Bern 65", "not_an_address", "Potsdamer Platz 2, 10785 Berlin"),
  stringsAsFactors = FALSE
)

locs <- geocode(x$address)
#> Address 'not_an_address' not found.

locs
#> Simple feature collection with 2 features and 10 fields
#> geometry type:  POINT
#> dimension:      XY
#> bbox:           xmin: 7.44657 ymin: 46.96138 xmax: 13.37525 ymax: 52.51005
#> epsg (SRID):    4326
#> proj4string:    +proj=longlat +datum=WGS84 +no_defs
#>                                        address          street houseNumber
#> 1    Wylerstrasse 123, 3014 Bern Bern, Schweiz    Wylerstrasse         123
#> 3 Potsdamer Platz 2, 10785 Berlin, Deutschland Potsdamer Platz           2
#>   postalCode   district   city          county  state country  type
#> 1       3014      Wyler   Bern Bern-Mittelland     BE     CHE point
#> 3      10785 Tiergarten Berlin          Berlin Berlin     DEU point
#>                    geometry
#> 1  POINT (7.44657 46.96138)
#> 3 POINT (13.37525 52.51005)

Using the row names of the returned sf object the initial data.frame can be added.

st_as_sf(data.frame(locs, x[row.names(locs), ]))
#> Simple feature collection with 2 features and 12 fields
#> geometry type:  POINT
#> dimension:      XY
#> bbox:           xmin: 7.44657 ymin: 46.96138 xmax: 13.37525 ymax: 52.51005
#> epsg (SRID):    4326
#> proj4string:    +proj=longlat +datum=WGS84 +no_defs
#>                                        address          street houseNumber
#> 1    Wylerstrasse 123, 3014 Bern Bern, Schweiz    Wylerstrasse         123
#> 3 Potsdamer Platz 2, 10785 Berlin, Deutschland Potsdamer Platz           2
#>   postalCode   district   city          county  state country  type
#> 1       3014      Wyler   Bern Bern-Mittelland     BE     CHE point
#> 3      10785 Tiergarten Berlin          Berlin Berlin     DEU point
#>                           company                       address.1
#> 1 Schweizerische Bundesbahnen SBB  Wylerstrasse 123, 3000 Bern 65
#> 3                Deutsche Bahn AG Potsdamer Platz 2, 10785 Berlin
#>                    geometry
#> 1  POINT (7.44657 46.96138)
#> 3 POINT (13.37525 52.51005)

Thank you for reporting this important issue.

dpprdan · 2019-11-19T17:44:52Z

Thanks!
However, merging on row.names seems to be unreliable, e.g. if one wants to retain the non-geocoded queries as well. I might be doing something wrong here, though?

library(hereR)
library(sf)
#> Linking to GEOS 3.6.1, GDAL 2.2.3, PROJ 4.9.3

x <- data.frame(
  company = c("Schweizerische Bundesbahnen SBB", "Bahnhof AG", "Deutsche Bahn AG"),
  address = c("Wylerstrasse 123, 3000 Bern 65", "not_an_address", "Potsdamer Platz 2, 10785 Berlin"),
  stringsAsFactors = FALSE
)

locs <- geocode(x$address)
#> Address 'not_an_address' not found.

merge(x, locs, all.x = TRUE, by = "row.names")
#>   Row.names                         company                       address.x
#> 1         1 Schweizerische Bundesbahnen SBB  Wylerstrasse 123, 3000 Bern 65
#> 2         2                      Bahnhof AG                  not_an_address
#> 3         3                Deutsche Bahn AG Potsdamer Platz 2, 10785 Berlin
#>                                      address.y          street houseNumber
#> 1    Wylerstrasse 123, 3014 Bern Bern, Schweiz    Wylerstrasse         123
#> 2 Potsdamer Platz 2, 10785 Berlin, Deutschland Potsdamer Platz           2
#> 3                                         <NA>            <NA>        <NA>
#>   postalCode   district   city          county  state country  type
#> 1       3014      Wyler   Bern Bern-Mittelland     BE     CHE point
#> 2      10785 Tiergarten Berlin          Berlin Berlin     DEU point
#> 3       <NA>       <NA>   <NA>            <NA>   <NA>    <NA>  <NA>
#>                    geometry
#> 1  POINT (7.44657 46.96138)
#> 2 POINT (13.37525 52.51005)
#> 3               POINT EMPTY

Anyway, using ‘real’ columns instead of row.names works better:

x$id <- rownames(x)
locs$id <- rownames(locs)

(y <- merge(x, locs, all.x = TRUE, by = "id"))
#>   id                         company                       address.x
#> 1  1 Schweizerische Bundesbahnen SBB  Wylerstrasse 123, 3000 Bern 65
#> 2  2                      Bahnhof AG                  not_an_address
#> 3  3                Deutsche Bahn AG Potsdamer Platz 2, 10785 Berlin
#>                                      address.y          street houseNumber
#> 1    Wylerstrasse 123, 3014 Bern Bern, Schweiz    Wylerstrasse         123
#> 2                                         <NA>            <NA>        <NA>
#> 3 Potsdamer Platz 2, 10785 Berlin, Deutschland Potsdamer Platz           2
#>   postalCode   district   city          county  state country  type
#> 1       3014      Wyler   Bern Bern-Mittelland     BE     CHE point
#> 2       <NA>       <NA>   <NA>            <NA>   <NA>    <NA>  <NA>
#> 3      10785 Tiergarten Berlin          Berlin Berlin     DEU point
#>                    geometry
#> 1  POINT (7.44657 46.96138)
#> 2               POINT EMPTY
#> 3 POINT (13.37525 52.51005)

In this simple example it would be possible to ~~rbind()~~ cbind() both objects, but that rests on the (fragile) assumption that both objects have the same nrow()

data.frame(locs, x[row.names(locs), ]) rests on a (IMO) similarly fragile assumption that the order (and number) of the rows of both objects remain unchanged. (Re “number”: The API may in principle return more than one result per query, try “Rathausmarkt, Hamburg” for example. Maybe you want to allow for multiple results in geocode() like you do in reverse_geocode() already?)

So adding an id column might be better (like you do with reverse_geocode())?

Also keep in mind that users might have duplicate addresses in their address vector (definitely saw a friend do this once). This speaks against adding the query/address vector to the result and merging by that.

Finally, reverse_geocode() has a similar problem. Imagine you have the name and
coordinates of some POIs and you would like to get a table with name and
address:

(z <- st_sf(y[c("company", "geometry")]))
#> Simple feature collection with 3 features and 1 field (with 1 geometry empty)
#> geometry type:  POINT
#> dimension:      XY
#> bbox:           xmin: 7.44657 ymin: 46.96138 xmax: 13.37525 ymax: 52.51005
#> epsg (SRID):    4326
#> proj4string:    +proj=longlat +datum=WGS84 +no_defs
#>                           company                  geometry
#> 1 Schweizerische Bundesbahnen SBB  POINT (7.44657 46.96138)
#> 2                      Bahnhof AG               POINT EMPTY
#> 3                Deutsche Bahn AG POINT (13.37525 52.51005)
resz <- reverse_geocode(z)
#> Warning in (function (res) : Request failed: HTTP status code 400.

How would you merge these, reliably? I’d suggest something along the lines of:

z$id <- seq_len(nrow(z))
resz$id <- c(1,3) # because the current id's represent the index of successful queries not the index of the POIs. So this would need fixing.
merge(st_drop_geometry(z), resz, by = "id")
#>   id                         company rank distance       level
#> 1  1 Schweizerische Bundesbahnen SBB    1        0 houseNumber
#> 2  3                Deutsche Bahn AG    1        0 houseNumber
#>                                          label country  state          county
#> 1    Wylerstrasse 123, 3014 Bern Bern, Schweiz     CHE     BE Bern-Mittelland
#> 2 Potsdamer Platz 2, 10785 Berlin, Deutschland     DEU Berlin          Berlin
#>     city   district          street houseNumber postalCode
#> 1   Bern      Wyler    Wylerstrasse         123       3014
#> 2 Berlin Tiergarten Potsdamer Platz           2      10785
#>                    geometry
#> 1  POINT (7.44657 46.96138)
#> 2 POINT (13.37525 52.51005)

Session info

devtools::session_info()
#> - Session info ---------------------------------------------------------------
#>  setting  value                       
#>  version  R version 3.6.1 (2019-07-05)
#>  os       Windows 10 x64              
#>  system   x86_64, mingw32             
#>  ui       RTerm                       
#>  language en                          
#>  collate  German_Germany.1252         
#>  ctype    German_Germany.1252         
#>  tz       Europe/Berlin               
#>  date     2019-11-19                  
#> 
#> - Packages -------------------------------------------------------------------
#>  package     * version    date       lib source                        
#>  assertthat    0.2.1      2019-03-21 [1] CRAN (R 3.6.1)                
#>  backports     1.1.5      2019-10-02 [1] CRAN (R 3.6.1)                
#>  callr         3.3.2      2019-09-22 [1] CRAN (R 3.6.1)                
#>  class         7.3-15     2019-01-01 [2] CRAN (R 3.6.1)                
#>  classInt      0.4-2      2019-10-17 [1] CRAN (R 3.6.1)                
#>  cli           1.1.0      2019-03-19 [1] CRAN (R 3.6.1)                
#>  codetools     0.2-16     2018-12-24 [1] CRAN (R 3.6.0)                
#>  crayon        1.3.4      2017-09-16 [1] CRAN (R 3.6.1)                
#>  curl          4.2        2019-09-24 [1] CRAN (R 3.6.1)                
#>  data.table    1.12.6     2019-10-18 [1] CRAN (R 3.6.1)                
#>  DBI           1.0.0      2018-05-02 [1] CRAN (R 3.6.1)                
#>  desc          1.2.0      2018-05-01 [1] CRAN (R 3.6.1)                
#>  devtools      2.2.1      2019-09-24 [1] CRAN (R 3.6.1)                
#>  digest        0.6.22     2019-10-21 [1] CRAN (R 3.6.1)                
#>  e1071         1.7-2      2019-06-05 [1] CRAN (R 3.6.1)                
#>  ellipsis      0.3.0      2019-09-20 [1] CRAN (R 3.6.1)                
#>  evaluate      0.14       2019-05-28 [1] CRAN (R 3.6.1)                
#>  fs            1.3.1      2019-05-06 [1] CRAN (R 3.6.1)                
#>  glue          1.3.1      2019-03-12 [1] CRAN (R 3.6.1)                
#>  hereR       * 0.2.0      2019-11-13 [1] CRAN (R 3.6.1)                
#>  highr         0.8        2019-03-20 [1] CRAN (R 3.6.1)                
#>  htmltools     0.4.0      2019-10-04 [1] CRAN (R 3.6.1)                
#>  jsonlite      1.6        2018-12-07 [1] CRAN (R 3.6.1)                
#>  KernSmooth    2.23-15    2015-06-29 [2] CRAN (R 3.6.1)                
#>  knitr         1.26       2019-11-12 [1] CRAN (R 3.6.1)                
#>  magrittr      1.5        2014-11-22 [1] CRAN (R 3.6.1)                
#>  memoise       1.1.0      2017-04-21 [1] CRAN (R 3.6.1)                
#>  pkgbuild      1.0.6      2019-10-09 [1] CRAN (R 3.6.1)                
#>  pkgload       1.0.2      2018-10-29 [1] CRAN (R 3.6.1)                
#>  prettyunits   1.0.2      2015-07-13 [1] CRAN (R 3.6.1)                
#>  processx      3.4.1      2019-07-18 [1] CRAN (R 3.6.1)                
#>  ps            1.3.0      2018-12-21 [1] CRAN (R 3.6.1)                
#>  R6            2.4.1      2019-11-12 [1] CRAN (R 3.6.1)                
#>  Rcpp          1.0.3      2019-11-08 [1] CRAN (R 3.6.1)                
#>  remotes       2.1.0.9000 2019-07-22 [1] Github (r-lib/remotes@6e9eaa9)
#>  rlang         0.4.1      2019-10-24 [1] CRAN (R 3.6.1)                
#>  rmarkdown     1.17       2019-11-13 [1] CRAN (R 3.6.1)                
#>  rprojroot     1.3-2      2018-01-03 [1] CRAN (R 3.6.1)                
#>  sessioninfo   1.1.1      2018-11-05 [1] CRAN (R 3.6.1)                
#>  sf          * 0.8-0      2019-09-17 [1] CRAN (R 3.6.1)                
#>  stringi       1.4.3      2019-03-12 [1] CRAN (R 3.6.0)                
#>  stringr       1.4.0      2019-02-10 [1] CRAN (R 3.6.1)                
#>  testthat      2.3.0      2019-11-05 [1] CRAN (R 3.6.1)                
#>  units         0.6-5      2019-10-08 [1] CRAN (R 3.6.1)                
#>  usethis       1.5.1      2019-07-04 [1] CRAN (R 3.6.1)                
#>  withr         2.1.2      2018-03-15 [1] CRAN (R 3.6.1)                
#>  xfun          0.11       2019-11-12 [1] CRAN (R 3.6.1)                
#>  yaml          2.2.0      2018-07-25 [1] CRAN (R 3.6.0)                
#> 
#> [1] C:/Users/daniel/Documents/.R/win-library
#> [2] C:/Program Files/R/R-3.6.1/library

dpprdan · 2019-11-19T17:46:31Z

Oh, I meant merge(st_drop_geometry(z), resz, all.x = TRUE, by = "id") for the last call.

munterfinger · 2019-12-08T15:17:17Z

Thanks for your feedback and sorry that it took me some time to answer.

Yes, merging using row.names seems to be a bad idea as it is inconsistent with respect to other functions of the package. Additionally the values of row.names are not considered in merge(x, locs, all.x = TRUE, by = "row.names"), instead the index of the row position is taken.

Since empty entries in the geometry column in sf objects are a bit cumbersome in my view, I would like to avoid them, which speaks against using data.table(type = NA_character_) in case geocoding fails or if addresses are formally invalid. The reason for this is that I assume that after geocoding a further spatial analysis follows. The sf package ignores empty geometries (as for example st_buffer()), but the NA cases should be handled explicitly. Locking empty geometries prompts the user to do so. However, this is a personal view.

Therefore I added an "id" column to the geocode output:

library(hereR)
library(sf)
#> Linking to GEOS 3.7.2, GDAL 2.4.2, PROJ 5.2.0

x <- data.frame(
  company = c("Schweizerische Bundesbahnen SBB", "Bahnhof AG", "Deutsche Bahn AG"),
  address = c("Wylerstrasse 123, 3000 Bern 65", "not_an_address", "Potsdamer Platz 2, 10785 Berlin"),
  stringsAsFactors = FALSE
)

(locs <- geocode(x$address))
#> Address(es) 'not_an_address' not found.
#> Simple feature collection with 2 features and 11 fields
#> geometry type:  POINT
#> dimension:      XY
#> bbox:           xmin: 7.44657 ymin: 46.96138 xmax: 13.37525 ymax: 52.51005
#> epsg (SRID):    4326
#> proj4string:    +proj=longlat +datum=WGS84 +no_defs
#>   id                                      address          street
#> 1  1    Wylerstrasse 123, 3014 Bern Bern, Schweiz    Wylerstrasse
#> 2  3 Potsdamer Platz 2, 10785 Berlin, Deutschland Potsdamer Platz
#>   houseNumber postalCode   district   city          county  state country
#> 1         123       3014      Wyler   Bern Bern-Mittelland     BE     CHE
#> 2           2      10785 Tiergarten Berlin          Berlin Berlin     DEU
#>    type                  geometry
#> 1 point  POINT (7.44657 46.96138)
#> 2 point POINT (13.37525 52.51005)

The column "id" matches the order of the the input addresses. Using the "id" column a corresponding data.frame "df" with the addresses to geocode could be joined to the coordinates after geocoding.

(y <- st_as_sf(data.frame(locs, x[locs$id, ])))
#> Simple feature collection with 2 features and 13 fields
#> geometry type:  POINT
#> dimension:      XY
#> bbox:           xmin: 7.44657 ymin: 46.96138 xmax: 13.37525 ymax: 52.51005
#> epsg (SRID):    4326
#> proj4string:    +proj=longlat +datum=WGS84 +no_defs
#>   id                                      address          street
#> 1  1    Wylerstrasse 123, 3014 Bern Bern, Schweiz    Wylerstrasse
#> 3  3 Potsdamer Platz 2, 10785 Berlin, Deutschland Potsdamer Platz
#>   houseNumber postalCode   district   city          county  state country
#> 1         123       3014      Wyler   Bern Bern-Mittelland     BE     CHE
#> 3           2      10785 Tiergarten Berlin          Berlin Berlin     DEU
#>    type                         company                       address.1
#> 1 point Schweizerische Bundesbahnen SBB  Wylerstrasse 123, 3000 Bern 65
#> 3 point                Deutsche Bahn AG Potsdamer Platz 2, 10785 Berlin
#>                    geometry
#> 1  POINT (7.44657 46.96138)
#> 3 POINT (13.37525 52.51005)

As for your last point:

Finally, reverse_geocode() has a similar problem. Imagine you have
the name and coordinates of some POIs and you would like to get a
table with name and address: resz$id <- c(1,3) # because the current id's represent the index of successful queries not the index of the POIs. So this would need fixing.

The result of reverese_geocode() can be joined to the input using the "id" column, also if there is an empty response from the API:

x <- data.frame(
  place = c("Barcelona", "Ocean", "Melbourne"),
  lng = c(2.173404, 76, 144.963058),
  lat = c(41.385063, -28, -37.813629)
) %>% st_as_sf(coords = c("lng", "lat")) %>% st_set_crs(4326)

y <- reverse_geocode(x, landmarks = TRUE, results = 3)

x$id <- seq(1, nrow(x))
(merge(st_drop_geometry(x), y, all.x = TRUE, by = "id"))
#>   id     place rank distance    level                        name
#> 1  1 Barcelona    1    101.0 landmark  Plaça de la Vila de Madrid
#> 2  1 Barcelona    2    276.2 landmark   Plaça de Sant Josep Oriol
#> 3  1 Barcelona    3    349.1 landmark   Plaça de Vicenç Martorell
#> 4  2     Ocean   NA       NA     <NA>                        <NA>
#> 5  3 Melbourne    1    455.2 landmark RMIT University City Campus
#> 6  3 Melbourne    2    617.4 landmark           Flagstaff Gardens
#> 7  3 Melbourne    3    654.3 landmark                 Yarra River
#>                                                             label country
#> 1                            08007 Barcelona (Barcelona), Espanya     ESP
#> 2 Plaça de Sant Josep Oriol, 08002 Barcelona (Barcelona), Espanya     ESP
#> 3  Carrer de les Ramelleres, 08001 Barcelona (Barcelona), Espanya     ESP
#> 4                                                            <NA>    <NA>
#> 5                                   Melbourne VIC 3000, Australia     AUS
#> 6                              West Melbourne VIC 3003, Australia     AUS
#> 7                                   Melbourne VIC 3000, Australia     AUS
#>       state                   geometry
#> 1 Catalunya   POINT (2.17221 41.38441)
#> 2 Catalunya   POINT (2.17413 41.38244)
#> 3 Catalunya     POINT (2.16903 41.384)
#> 4      <NA>                POINT EMPTY
#> 5       VIC POINT (144.9648 -37.80718)
#> 6       VIC POINT (144.9544 -37.81043)
#> 7       VIC POINT (144.9407 -37.81627)

The problem starts if an API request fails. My first guess to fix this is to avoid empty geometries in the input of reverese_geocode() by checking the sf object via st_is_empty() (see #16).

But there are other possibilities for a failed request and these also must be handled, which means .get_content() has to be adjusted (see #17).

Session info

devtools::session_info()
#> ─ Session info ──────────────────────────────────────────────────────────
#>  setting  value                       
#>  version  R version 3.6.1 (2019-07-05)
#>  os       macOS Catalina 10.15.1      
#>  system   x86_64, darwin15.6.0        
#>  ui       X11                         
#>  language (EN)                        
#>  collate  de_CH.UTF-8                 
#>  ctype    de_CH.UTF-8                 
#>  tz       Europe/Zurich               
#>  date     2019-12-08                  
#> 
#> ─ Packages ──────────────────────────────────────────────────────────────
#>  package     * version    date       lib source        
#>  assertthat    0.2.1      2019-03-21 [1] CRAN (R 3.6.0)
#>  backports     1.1.5      2019-10-02 [1] CRAN (R 3.6.0)
#>  callr         3.3.2      2019-09-22 [1] CRAN (R 3.6.0)
#>  class         7.3-15     2019-01-01 [1] CRAN (R 3.6.1)
#>  classInt      0.4-2      2019-10-17 [1] CRAN (R 3.6.0)
#>  cli           1.1.0      2019-03-19 [1] CRAN (R 3.6.0)
#>  crayon        1.3.4      2017-09-16 [1] CRAN (R 3.6.0)
#>  curl          4.2        2019-09-24 [1] CRAN (R 3.6.0)
#>  data.table    1.12.6     2019-10-18 [1] CRAN (R 3.6.0)
#>  DBI           1.0.0      2018-05-02 [1] CRAN (R 3.6.0)
#>  desc          1.2.0      2018-05-01 [1] CRAN (R 3.6.0)
#>  devtools      2.2.1      2019-09-24 [1] CRAN (R 3.6.0)
#>  digest        0.6.22     2019-10-21 [1] CRAN (R 3.6.0)
#>  e1071         1.7-2      2019-06-05 [1] CRAN (R 3.6.0)
#>  ellipsis      0.3.0      2019-09-20 [1] CRAN (R 3.6.0)
#>  evaluate      0.14       2019-05-28 [1] CRAN (R 3.6.0)
#>  fs            1.3.1      2019-05-06 [1] CRAN (R 3.6.0)
#>  glue          1.3.1      2019-03-12 [1] CRAN (R 3.6.0)
#>  hereR       * 0.2.0.9000 2019-12-08 [1] local         
#>  htmltools     0.4.0      2019-10-04 [1] CRAN (R 3.6.0)
#>  jsonlite      1.6        2018-12-07 [1] CRAN (R 3.6.0)
#>  KernSmooth    2.23-16    2019-10-15 [1] CRAN (R 3.6.0)
#>  knitr         1.25       2019-09-18 [1] CRAN (R 3.6.0)
#>  magrittr      1.5        2014-11-22 [1] CRAN (R 3.6.0)
#>  memoise       1.1.0      2017-04-21 [1] CRAN (R 3.6.0)
#>  pkgbuild      1.0.6      2019-10-09 [1] CRAN (R 3.6.0)
#>  pkgload       1.0.2      2018-10-29 [1] CRAN (R 3.6.0)
#>  prettyunits   1.0.2      2015-07-13 [1] CRAN (R 3.6.0)
#>  processx      3.4.1      2019-07-18 [1] CRAN (R 3.6.0)
#>  ps            1.3.0      2018-12-21 [1] CRAN (R 3.6.0)
#>  R6            2.4.1      2019-11-12 [1] CRAN (R 3.6.0)
#>  Rcpp          1.0.3      2019-11-08 [1] CRAN (R 3.6.0)
#>  remotes       2.1.0      2019-06-24 [1] CRAN (R 3.6.0)
#>  rlang         0.4.1      2019-10-24 [1] CRAN (R 3.6.0)
#>  rmarkdown     1.16       2019-10-01 [1] CRAN (R 3.6.0)
#>  rprojroot     1.3-2      2018-01-03 [1] CRAN (R 3.6.0)
#>  sessioninfo   1.1.1      2018-11-05 [1] CRAN (R 3.6.0)
#>  sf          * 0.8-0      2019-09-17 [1] CRAN (R 3.6.0)
#>  stringi       1.4.3      2019-03-12 [1] CRAN (R 3.6.0)
#>  stringr       1.4.0      2019-02-10 [1] CRAN (R 3.6.0)
#>  testthat      2.2.1      2019-07-25 [1] CRAN (R 3.6.0)
#>  units         0.6-5      2019-10-08 [1] CRAN (R 3.6.0)
#>  usethis       1.5.1      2019-07-04 [1] CRAN (R 3.6.0)
#>  withr         2.1.2      2018-03-15 [1] CRAN (R 3.6.0)
#>  xfun          0.10       2019-10-01 [1] CRAN (R 3.6.0)
#>  yaml          2.2.0      2018-07-25 [1] CRAN (R 3.6.0)
#> 
#> [1] /Library/Frameworks/R.framework/Versions/3.6/Resources/library

Add an "id" column to the output of geocode(), closes #9.

dpprdan mentioned this issue Nov 7, 2019

Return an empty instead of a NULL response when geocoding? #10

Closed

munterfinger self-assigned this Nov 8, 2019

munterfinger added the enhancement label Nov 9, 2019

munterfinger closed this in 76cb755 Nov 9, 2019

munterfinger added a commit that referenced this issue Nov 12, 2019

Update geocoder vignette with example from issue #9

0930742

munterfinger reopened this Nov 25, 2019

munterfinger closed this in 1b82a99 Dec 8, 2019

munterfinger / hereR

add query column to `geocode()` result? #9

add query column to `geocode()` result? #9

dpprdan commented Nov 7, 2019

munterfinger commented Nov 9, 2019

dpprdan commented Nov 19, 2019

dpprdan commented Nov 19, 2019

munterfinger commented Dec 8, 2019 •

edited

munterfinger / hereR

Join GitHub today

add query column to `geocode()` result? #9

add query column to `geocode()` result? #9

Comments

dpprdan commented Nov 7, 2019

munterfinger commented Nov 9, 2019

dpprdan commented Nov 19, 2019

dpprdan commented Nov 19, 2019

munterfinger commented Dec 8, 2019 • edited

Essential cookies

Always active

Analytics cookies

munterfinger commented Dec 8, 2019 •

edited