Error for convert geoJSON to data.frame from shapefile original dataset-CodePudding

I'd like to convert a shapefile (sel_stands_CMPC.shp) to geoJSON and after to data.frame, but the the list to data.frame I have the error of differing number of rows. I need geoJSON and dataframe data, then is not the case of shapefile to dataframe simple conversion. I try to do:

library(sf)
library(geojsonsf)
library(plyr)
library(geojsonR)

# get AOI in shapefile
download.file(
  "https://github.com/Leprechault/trash/raw/main/sel_stands_CMPC.zip",
  zip_path <- tempfile(fileext = ".zip")
)
unzip(zip_path, exdir = tempdir())

# Open the file
setwd(tempdir())
stands_sel <- st_read("sel_stands_CMPC.shp")
# Reading layer `sel_stands_CMPC' from data source `C:\Users\fores\AppData\Local\Temp\Rtmp6l1bGx\sel_stands_CMPC.shp' using driver `ESRI Shapefile'
# Simple feature collection with 2 features and 16 fields
# Geometry type: MULTIPOLYGON
# Dimension:     XY
# Bounding box:  xmin: -52.3284 ymin: -30.43305 xmax: -51.21323 ymax: -30.35118
# Geodetic CRS:  GCS_unknown

# Open as geoJSON
geo <- sf_geojson(stands_sel)

# Convert to data frame for *CSV export
geo_js_df <- plyr::ldply(FROM_GeoJson(geo), data.frame)
# Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE,  : 
#   arguments imply differing number of rows: 144, 62, 29

CodePudding user response：

Not sure if this is what you are looking for, but here is a suggestion:

REPREX

# Convert 'geo" into 'wkt' and then 'data.frame'
geo_js_df <- as.data.frame(geojson_wkt(geo))

And the output looks like this:

# Output structure
str(geo_js_df)
#> 'data.frame':    2 obs. of  17 variables:
#>  $ SISTEMA_PR: chr  "MACRO ESTACA - EUCALIPTO" "SEMENTE - EUCALIPTO"
#>  $ ESPECIE   : chr  "SALIGNA" "DUNNI"
#>  $ ID_UNIQUE : chr  "BARBANEGRA159A" "CAMPOSECO016A"
#>  $ CICLO     : num  2 1
#>  $ LOCALIDADE: chr  "BARRA DO RIBEIRO" "DOM FELICIANO"
#>  $ ROTACAO   : num  1 1
#>  $ CARACTER_1: chr  "Produtivo" "Produtivo"
#>  $ VLR_AREA  : num  8.53 28.07
#>  $ ID_REGIAO : num  11 11
#>  $ CD_USO_SOL: num  2433 9053
#>  $ DATA_PLANT: chr  "2008/04/15" "2010/04/15"
#>  $ ID_PROJETO: chr  "002" "344"
#>  $ CARACTERIS: chr  "Plantio Comercial" "Plantio Comercial"
#>  $ PROJETO   : chr  "BARBA NEGRA" "CAMPO SECO"
#>  $ ESPACAMENT: chr  "3.00 x 2.50" "3.5 x 2.14"
#>  $ CD_TALHAO : chr  "159A" "016A"
#>  $ geometry  :List of 2
#>   ..$ : 'wkt' chr "MULTIPOLYGON (((-51.2142 -30.3517,-51.2143 -30.3518,-51.2143 -30.3518,-51.2143 -30.3519,-51.2143 -30.3519,-51.2"| __truncated__
#>   ..$ : 'wkt' chr "MULTIPOLYGON (((-52.3214 -30.4271,-52.3214 -30.4272,-52.3214 -30.4272,-52.3215 -30.4272,-52.3215 -30.4272,-52.3"| __truncated__
#>  - attr(*, "wkt_column")= chr "geometry"

^{Created on 2021-10-09 by the reprex package (v2.0.1)}

CodePudding user response：

The same can be achieved with:

geo_df2 <-as.data.frame( sf::st_read(geo, quiet=TRUE))

 str(geo_df2)
'data.frame':   2 obs. of  17 variables:
 $ CD_USO_SOL: num  2433 9053
 $ ID_REGIAO : num  11 11
 $ ID_PROJETO: chr  "002" "344"
 $ PROJETO   : chr  "BARBA NEGRA" "CAMPO SECO"
 $ CD_TALHAO : chr  "159A" "016A"
 $ CARACTERIS: chr  "Plantio Comercial" "Plantio Comercial"
 $ CARACTER_1: chr  "Produtivo" "Produtivo"
 $ CICLO     : int  2 1
 $ ROTACAO   : int  1 1
 $ DATA_PLANT: Date, format: "2008-04-15" "2010-04-15"
 $ LOCALIDADE: chr  "BARRA DO RIBEIRO" "DOM FELICIANO"
 $ ESPACAMENT: chr  "3.00 x 2.50" "3.5 x 2.14"
 $ ESPECIE   : chr  "SALIGNA" "DUNNI"
 $ SISTEMA_PR: chr  "MACRO ESTACA - EUCALIPTO" "SEMENTE - EUCALIPTO"
 $ VLR_AREA  : num  8.53 28.07
 $ ID_UNIQUE : chr  "BARBANEGRA159A" "CAMPOSECO016A"
 $ geometry  :sfc_MULTIPOLYGON of length 2; first list element: List of 3
  ..$ :List of 1
  .. ..$ : num [1:144, 1:2] -51.2 -51.2 -51.2 -51.2 -51.2 ...
  ..$ :List of 1
  .. ..$ : num [1:62, 1:2] -51.2 -51.2 -51.2 -51.2 -51.2 ...
  ..$ :List of 1
  .. ..$ : num [1:29, 1:2] -51.2 -51.2 -51.2 -51.2 -51.2 ...
  ..- attr(*, "class")= chr [1:3] "XY" "MULTIPOLYGON" "sfg"
 - attr(*, "sf_column")= chr "geometry"
 - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
  ..- attr(*, "names")= chr [1:16] "CD_USO_SOL" "ID_REGIAO" "ID_PROJETO" "PROJETO" ...
write.csv(geo_df2, 'Barra_do_Ribeiro_Dom_Feliciano.csv')

depending on your further use. And I got all the errors you did and then some more.