dealing with nested json columns after reading with geojsonsf

[frabau1]

I'm working with a geojson file and reading it with geojsonsf. The file is importing successfully, but there are still nested json columns in the data frame. I'm not sure this is an issue with the geojsonsf package, but wanted to see if the team had any suggestions on how to unnest the additional columns.

library(geojsonsf)

link <- 'https://tiles.skimap.org/geojson/ski_areas.geojson'

S0 <- geojson_sf(link, expand_geometries = TRUE) 

[dcooley]

please see this issue - I initially decided to follow {sf}'s lead and convert nested properties in to strings. And I'm not sure if an {sf} object can handle nested / list columns.

A work-around is something like

lst <- jsonify::from_json(link)

coords <- lst$features$geometry$coordinates

sfc_points <- sfheaders::sf_point(matrix(unlist(coords), ncol = 2, byrow = T))

lst$geometry <- sfc_points

[frabau1]

Dave, Thanks for getting back to me - I really appreciate it. I figured out the issue this afternoon - the file I was reading had an odd format on a couple of the fields so they didn’t read in correctly. When I read the file with geojsonsf it put the data into a column with curly { brackets but not square [ brackets. Not having the square [ bracket kept all of the things I tried initially from working as they were not recognized as JSON format. I pasted a leading and trailing square bracket on to each observation and was able to feed that through tidyjson gather and spread to get the data into columns and then join it back on the original data frame. I don’t think it is necessarily an issue with geojsonsf, but just in case you want to see what I was working with I did I will include my code below Thanks again for following up! Frank Baumgardner

…

--------------------------------- library(tidyjson) library(tidyr) library(dplyr) library(geojsonsf) library(sf) link <- 'https://tiles.skimap.org/geojson/ski_areas.geojson' S0 <- geojson_sf(link) st_crs(S0) #make a copy to save the inital file S1 <- S0 #location's format needs brackets to process S1$location2 <- ifelse(is.na(S1$location), NA, paste0('[', S1$location,']')) #gather won't work if you keep the geometry S2 <- st_drop_geometry(S1) #Select the id column along with the json columns we need to parse S2 <- S2 %>% select(id, location2, statistics2) #you can't gather na's so drop them - we will join on id later S3.loc <- S2 %>% filter(!is.na(S2$location2)) %>% select(id, location2) #Gather & Spread S3.loc$json <- gather_array(S3.loc$location2) S4.loc <- S3.loc$json %>% spread_all S5.loc <- as.data.frame(S4.loc) S6.loc <- cbind(S3.loc, S5.loc) S7.loc <- S6.loc[-c(2:7)]

On Jan 3, 2023, at 3:11 PM, Dave ***@***.***> wrote: please see this issue <#17> - I initially decided to follow {sf}'s lead and convert nested properties in to strings. And I'm not sure if an {sf} object can handle nested / list columns. A work-around is something like lst <- jsonify::from_json(link) coords <- lst$features$geometry$coordinates sfc_points <- sfheaders::sf_point(matrix(unlist(coords), ncol = 2, byrow = T)) lst$geometry <- sfc_points — Reply to this email directly, view it on GitHub <#97 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AZN7WNICK2WQ5N43O7IF4HDWQSBW7ANCNFSM6AAAAAATQATZKM>. You are receiving this because you authored the thread.