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jessecambon / tidygeocoder

Geocoding Made Easy
https://jessecambon.github.io/tidygeocoder
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reverse_geocode not working #175

Closed xiaochuanfang closed 2 years ago

xiaochuanfang commented 2 years ago

I tried the example from https://cran.r-project.org/web/packages/tidygeocoder/readme/README.html. But the address_found returned NA.

The data was: name addr latitude longitude White House 1600 Pennsylvania Ave NW, Washington, DC 38.89770 -77.03655 Transamerica Pyramid 600 Montgomery St, San Francisco, CA 94111 37.79520 -122.40279 Willis Tower 233 S Wacker Dr, Chicago, IL 60606 41.87535 -87.63576

The code was: reverse <- lat_longs %>% reverse_geocode(lat = latitude, long = longitude, method = 'osm', address = address_found, full_results = TRUE)

jessecambon commented 2 years ago

Hi @xiaochuanfang has this happened multiple times? Can you please post the results of devtools::session_info()?

xiaochuanfang commented 2 years ago

This is the first time I use tidygeocoder. Not sure something wrong on my side? setting value version R version 4.2.0 (2022-04-22 ucrt) os Windows 10 x64 (build 22000) system x86_64, mingw32 ui RStudio language (EN) collate English_United States.utf8 ctype English_United States.utf8 tz America/New_York date 2022-08-05 rstudio 2022.07.1+554 Spotted Wakerobin (desktop) pandoc NA

─ Packages ────────────────────────────────────────────────────────────────────────── package version date (UTC) lib source assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.2.0) cachem 1.0.6 2021-08-19 [1] CRAN (R 4.2.1) callr 3.7.0 2021-04-20 [1] CRAN (R 4.2.0) cli 3.3.0 2022-04-25 [1] CRAN (R 4.2.0) crayon 1.5.1 2022-03-26 [1] CRAN (R 4.2.0) curl 4.3.2 2021-06-23 [1] CRAN (R 4.2.0) DBI 1.1.3 2022-06-18 [1] CRAN (R 4.2.0) devtools 2.4.4 2022-07-20 [1] CRAN (R 4.2.1) digest 0.6.29 2021-12-01 [1] CRAN (R 4.2.0) dplyr 1.0.9 2022-04-28 [1] CRAN (R 4.2.0) ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.2.0) fansi 1.0.3 2022-03-24 [1] CRAN (R 4.2.0) fastmap 1.1.0 2021-01-25 [1] CRAN (R 4.2.0) fs 1.5.2 2021-12-08 [1] CRAN (R 4.2.0) generics 0.1.2 2022-01-31 [1] CRAN (R 4.2.0) glue 1.6.2 2022-02-24 [1] CRAN (R 4.2.0) hms 1.1.1 2021-09-26 [1] CRAN (R 4.2.0) htmltools 0.5.2 2021-08-25 [1] CRAN (R 4.2.0) htmlwidgets 1.5.4 2021-09-08 [1] CRAN (R 4.2.1) httpuv 1.6.5 2022-01-05 [1] CRAN (R 4.2.1) httr 1.4.3 2022-05-04 [1] CRAN (R 4.2.0) jsonlite 1.8.0 2022-02-22 [1] CRAN (R 4.2.0) later 1.3.0 2021-08-18 [1] CRAN (R 4.2.1) lifecycle 1.0.1 2021-09-24 [1] CRAN (R 4.2.0) magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.2.0) memoise 2.0.1 2021-11-26 [1] CRAN (R 4.2.1) mime 0.12 2021-09-28 [1] CRAN (R 4.2.0) miniUI 0.1.1.1 2018-05-18 [1] CRAN (R 4.2.1) pillar 1.7.0 2022-02-01 [1] CRAN (R 4.2.0) pkgbuild 1.3.1 2021-12-20 [1] CRAN (R 4.2.1) pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.2.0) pkgload 1.3.0 2022-06-27 [1] CRAN (R 4.2.1) prettyunits 1.1.1 2020-01-24 [1] CRAN (R 4.2.0) processx 3.6.1 2022-06-17 [1] CRAN (R 4.2.0) profvis 0.3.7 2020-11-02 [1] CRAN (R 4.2.1) progress 1.2.2 2019-05-16 [1] CRAN (R 4.2.0) promises 1.2.0.1 2021-02-11 [1] CRAN (R 4.2.1) ps 1.7.1 2022-06-18 [1] CRAN (R 4.2.0) purrr 0.3.4 2020-04-17 [1] CRAN (R 4.2.0) R6 2.5.1 2021-08-19 [1] CRAN (R 4.2.0) Rcpp 1.0.8.3 2022-03-17 [1] CRAN (R 4.2.0) remotes 2.4.2 2021-11-30 [1] CRAN (R 4.2.1) rlang 1.0.4 2022-07-12 [1] CRAN (R 4.2.1) rstudioapi 0.13 2020-11-12 [1] CRAN (R 4.2.0) sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.2.1) shiny 1.7.2 2022-07-19 [1] CRAN (R 4.2.1) stringi 1.7.6 2021-11-29 [1] CRAN (R 4.2.0) stringr 1.4.0 2019-02-10 [1] CRAN (R 4.2.0) tibble 3.1.7 2022-05-03 [1] CRAN (R 4.2.0) tidygeocoder 1.0.5 2021-11-02 [1] CRAN (R 4.2.1) tidyselect 1.1.2 2022-02-21 [1] CRAN (R 4.2.0) urlchecker 1.0.1 2021-11-30 [1] CRAN (R 4.2.1) usethis * 2.1.6 2022-05-25 [1] CRAN (R 4.2.1) utf8 1.2.2 2021-07-24 [1] CRAN (R 4.2.0) vctrs 0.4.1 2022-04-13 [1] CRAN (R 4.2.0) xtable 1.8-4 2019-04-21 [1] CRAN (R 4.2.0)

[1] C:/Users/xiaoc/AppData/Local/R/win-library/4.2 [2] C:/Program Files/R/R-4.2.0/library

xiaochuanfang commented 2 years ago

Code: data <- read.csv (paste (path, "sample2.csv", sep = "")) reverse <- data %>% reverse_geocode(lat = longitude, long = latitude, method = 'osm', address = address_found, full_results = TRUE) reverse

Sample2.csv: name | addr | latitude | longitude White House | 1600 Pennsylvania Ave NW, Washington, DC | 38.8977 | -77.03655 Transamerica Pyramid | 600 Montgomery St, San Francisco, CA 94111 | 37.7952 | -122.4028 Willis Tower | 233 S Wacker Dr, Chicago, IL 60606 | 41.8754 | -87.63576

R script result:

A tibble: 3 × 5

name addr latitude longitude address_found

1 White House 1600 Pennsylvania Ave NW, Wash… 38.9 -77.0 NA 2 Transamerica Pyramid 600 Montgomery St, San Francis… 37.8 -122. NA 3 Willis Tower 233 S Wacker Dr, Chicago, IL 6… 41.9 -87.6 NA
jessecambon commented 2 years ago

Hmm I don't notice any obvious issues with your package versions. What happens if you run this?

reverse_geo(lat = 38.895865, long = -77.0307713, method = "osm")

See expected results in the examples here: https://jessecambon.github.io/tidygeocoder/reference/reverse_geo.html

You could also try to update all your packages to see if that resolves the issue.

xiaochuanfang commented 2 years ago

I'm able to get A tibble: 1 × 3 lat long address

1 38.9 -77.0 Pennsylvania Avenue, Washington, District of Columbia, 20045, United Sta…
jessecambon commented 2 years ago

Hi @xiaochuanfang were you able to get this working? If so, what was the solution?

xiaochuanfang commented 2 years ago

No, I can't get it work. So I'm going work with the reverse_geo function from the tidygeocoder. You also facing the same problem too?

jessecambon commented 2 years ago

No I wasn't able to reproduce your issue. You are able to get results with reverse_geo but not reverse_geocode? With the same inputs?

xiaochuanfang commented 2 years ago
Same input but reverse_geo worked while reverse_geocode doesn't work for me. csv: latitude longitude address
38.895865 -77.0307713

Code: sample <- read.csv (paste (path, "sample3.csv", sep = "")) reverse <- sample %>% reverse_geocode(lat = longitude, long = latitude, method = 'osm', address = address_found, full_results = TRUE) reverse

Result:

A tibble: 1 × 4

latitude longitude address address_found

1 38.9 -77.0 NA NA
jessecambon commented 2 years ago

That is odd. Are you able to run the examples in the reverse_geocode documentation?

https://jessecambon.github.io/tidygeocoder/reference/reverse_geocode.html

library(tibble)
library(dplyr, warn.conflicts = FALSE)

tibble(
  latitude = c(38.895865, 43.6534817),
  longitude = c(-77.0307713, -79.3839347)
) %>%
  reverse_geocode(
    lat = latitude,
    long = longitude,
    method = "osm",
    full_results = TRUE
  )
xiaochuanfang commented 2 years ago

I think this one works:

A tibble: 2 × 22

latitude longitude address place_id licence osm_type osm_id osm_lat osm_lon road city state

1 38.9 -77.0 Pennsylvania … 2.25e8 Data ©… way 5.65e8 38.895… -77.03… Penn… Wash… Dist… 2 43.7 -79.4 Toronto City … 1.53e8 Data ©… way 1.99e8 43.653… -79.38… Quee… Old … Onta… # … with 10 more variables: `ISO3166-2-lvl4` , postcode , country , # country_code , boundingbox , amenity , house_number , neighbourhood , # quarter , state_district
jessecambon commented 2 years ago

That's good. Since that works, I'm guessing there may be an issue with the data frame that you pass to reverse_geocode (when you get NA results). You could print the values of the latitude and longitude columns to the screen and see if you spot anything.

If that doesn't reveal the problem then see if you can make a reproducible example with the reprex package:

https://www.tidyverse.org/help/

xiaochuanfang commented 2 years ago

Oh yes. I already asked in stackoverflow. https://stackoverflow.com/questions/73255542/unknown-issue-prevents-geocode-reverse-from-working. So far haven't heard an acceptable answer yet.