Read simple features or layers from file or database

Read simple features from file or database, or retrieve layer names and their geometry type(s)

Read PostGIS table directly through DBI and RPostgreSQL interface, converting Well-Know Binary geometries to sfc

st_read(dsn, layer, ...)

# S3 method for character
st_read(
  dsn,
  layer,
  ...,
  query = NA,
  options = NULL,
  quiet = FALSE,
  geometry_column = 1L,
  type = 0,
  promote_to_multi = TRUE,
  stringsAsFactors = default.stringsAsFactors(),
  int64_as_string = FALSE,
  check_ring_dir = FALSE,
  fid_column_name = character(0),
  drivers = character(0),
  wkt_filter = character(0)
)

read_sf(..., quiet = TRUE, stringsAsFactors = FALSE, as_tibble = TRUE)

# S3 method for DBIObject
st_read(
  dsn = NULL,
  layer = NULL,
  query = NULL,
  EWKB = TRUE,
  quiet = TRUE,
  as_tibble = FALSE,
  geometry_column = NULL,
  ...
)

Arguments

dsn	data source name (interpretation varies by driver - for some drivers, dsn is a file name, but may also be a folder, or contain the name and access credentials of a database); in case of GeoJSON, dsn may be the character string holding the geojson data. It can also be an open database connection.
layer	layer name (varies by driver, may be a file name without extension); in case layer is missing, st_read will read the first layer of dsn, give a warning and (unless quiet = TRUE) print a message when there are multiple layers, or give an error if there are no layers in dsn. If dsn is a database connection, then layer can be a table name or a database identifier (see Id). It is also possible to omit layer and rather use the query argument.
...	parameter(s) passed on to st_as_sf
query	SQL query to select records; see details
options	character; driver dependent dataset open options, multiple options supported. For possible values, see the "Open options" section of the GDAL documentation of the corresponding driver, and https://github.com/r-spatial/sf/issues/1157 for an example.
quiet	logical; suppress info on name, driver, size and spatial reference, or signaling no or multiple layers
geometry_column	integer or character; in case of multiple geometry fields, which one to take?
type	integer; ISO number of desired simple feature type; see details. If left zero, and promote_to_multi is TRUE, in case of mixed feature geometry types, conversion to the highest numeric type value found will be attempted. A vector with different values for each geometry column can be given.
promote_to_multi	logical; in case of a mix of Point and MultiPoint, or of LineString and MultiLineString, or of Polygon and MultiPolygon, convert all to the Multi variety; defaults to TRUE
stringsAsFactors	logical; logical: should character vectors be converted to factors? The `factory-fresh' default is TRUE for st_read and FALSE for read_sf, but this can be changed globally by e.g. the R command options(stringsAsFactors = FALSE).
int64_as_string	logical; if TRUE, Int64 attributes are returned as string; if FALSE, they are returned as double and a warning is given when precision is lost (i.e., values are larger than 2^53).
check_ring_dir	logical; if TRUE, polygon ring directions are checked and if necessary corrected (when seen from above: exterior ring counter clockwise, holes clockwise)
fid_column_name	character; name of column to write feature IDs to; defaults to not doing this
drivers	character; limited set of driver short names to be tried (default: try all)
wkt_filter	character; WKT representation of a spatial filter (may be used as bounding box, selecting overlapping geometries); see examples
as_tibble	logical; should the returned table be of class tibble or data.frame?
EWKB	logical; is the WKB of type EWKB? if missing, defaults to TRUE

Value

object of class sf when a layer was successfully read; in case argument layer is missing and data source dsn does not contain a single layer, an object of class sf_layers is returned with the layer names, each with their geometry type(s). Note that the number of layers may also be zero.

Details

for geometry_column, see also https://trac.osgeo.org/gdal/wiki/rfc41_multiple_geometry_fields

for values for type see https://en.wikipedia.org/wiki/Well-known_text#Well-known_binary, but note that not every target value may lead to successful conversion. The typical conversion from POLYGON (3) to MULTIPOLYGON (6) should work; the other way around (type=3), secondary rings from MULTIPOLYGONS may be dropped without warnings. promote_to_multi is handled on a per-geometry column basis; type may be specified for each geometry column.

Note that stray files in data source directories (such as *.dbf) may lead to spurious errors that accompanying *.shp are missing.

In case of problems reading shapefiles from USB drives on OSX, please see https://github.com/r-spatial/sf/issues/252.

For query with a character dsn the query text is handed to 'ExecuteSQL' on the GDAL/OGR data set and will result in the creation of a new layer (and layer is ignored). See 'OGRSQL' https://gdal.org/user/ogr_sql_dialect.html for details. Please note that the 'FID' special field is driver-dependent, and may be either 0-based (e.g. ESRI Shapefile), 1-based (e.g. MapInfo) or arbitrary (e.g. OSM). Other features of OGRSQL are also likely to be driver dependent. The available layer names may be obtained with st_layers. Care will be required to properly escape the use of some layer names.

read_sf and write_sf are aliases for st_read and st_write, respectively, with some modified default arguments. read_sf and write_sf are quiet by default: they do not print information about the data source. read_sf returns an sf-tibble rather than an sf-data.frame. write_sf delete layers by default: it overwrites existing files without asking or warning.

if table is not given but query is, the spatial reference system (crs) of the table queried is only available in case it has been stored into each geometry record (e.g., by PostGIS, when using EWKB)

The function will automatically find the `geometry` type columns for drivers that support it. For the other drivers, it will try to cast all the character columns, which can be slow for very wide tables.

Note

The use of system.file in examples make sure that examples run regardless where R is installed: typical users will not use system.file but give the file name directly, either with full path or relative to the current working directory (see getwd). "Shapefiles" consist of several files with the same basename that reside in the same directory, only one of them having extension .shp.

See also

st_layers, st_drivers

Examples

nc = st_read(system.file("shape/nc.shp", package="sf"))
#> Reading layer `nc' from data source `/tmp/RtmpCdQsky/temp_libpath64f92385e079/sf/shape/nc.shp' using driver `ESRI Shapefile'
#> Simple feature collection with 100 features and 14 fields
#> geometry type:  MULTIPOLYGON
#> dimension:      XY
#> bbox:           xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
#> CRS:            4267
summary(nc) # note that AREA was computed using Euclidian area on lon/lat degrees
#>       AREA          PERIMETER         CNTY_         CNTY_ID            NAME   
#>  Min.   :0.0420   Min.   :0.999   Min.   :1825   Min.   :1825   Alamance : 1  
#>  1st Qu.:0.0910   1st Qu.:1.324   1st Qu.:1902   1st Qu.:1902   Alexander: 1  
#>  Median :0.1205   Median :1.609   Median :1982   Median :1982   Alleghany: 1  
#>  Mean   :0.1263   Mean   :1.673   Mean   :1986   Mean   :1986   Anson    : 1  
#>  3rd Qu.:0.1542   3rd Qu.:1.859   3rd Qu.:2067   3rd Qu.:2067   Ashe     : 1  
#>  Max.   :0.2410   Max.   :3.640   Max.   :2241   Max.   :2241   Avery    : 1  
#>                                                                 (Other)  :94  
#>       FIPS        FIPSNO         CRESS_ID          BIR74           SID74      
#>  37001  : 1   Min.   :37001   Min.   :  1.00   Min.   :  248   Min.   : 0.00  
#>  37003  : 1   1st Qu.:37050   1st Qu.: 25.75   1st Qu.: 1077   1st Qu.: 2.00  
#>  37005  : 1   Median :37100   Median : 50.50   Median : 2180   Median : 4.00  
#>  37007  : 1   Mean   :37100   Mean   : 50.50   Mean   : 3300   Mean   : 6.67  
#>  37009  : 1   3rd Qu.:37150   3rd Qu.: 75.25   3rd Qu.: 3936   3rd Qu.: 8.25  
#>  37011  : 1   Max.   :37199   Max.   :100.00   Max.   :21588   Max.   :44.00  
#>  (Other):94                                                                   
#>     NWBIR74           BIR79           SID79          NWBIR79       
#>  Min.   :   1.0   Min.   :  319   Min.   : 0.00   Min.   :    3.0  
#>  1st Qu.: 190.0   1st Qu.: 1336   1st Qu.: 2.00   1st Qu.:  250.5  
#>  Median : 697.5   Median : 2636   Median : 5.00   Median :  874.5  
#>  Mean   :1050.8   Mean   : 4224   Mean   : 8.36   Mean   : 1352.8  
#>  3rd Qu.:1168.5   3rd Qu.: 4889   3rd Qu.:10.25   3rd Qu.: 1406.8  
#>  Max.   :8027.0   Max.   :30757   Max.   :57.00   Max.   :11631.0  
#>                                                                    
#>           geometry  
#>  MULTIPOLYGON :100  
#>  epsg:4267    :  0  
#>  +proj=long...:  0  
#>                     
#>                     
#>                     
#>                     

## only three fields by select clause
## only two features by where clause
nc_sql = st_read(system.file("shape/nc.shp", package="sf"),
                     query = "SELECT NAME, SID74, FIPS FROM \"nc\" WHERE BIR74 > 20000")
#> Reading layer `nc' from data source `/tmp/RtmpCdQsky/temp_libpath64f92385e079/sf/shape/nc.shp' using driver `ESRI Shapefile'
#> Simple feature collection with 2 features and 3 fields
#> geometry type:  POLYGON
#> dimension:      XY
#> bbox:           xmin: -81.06555 ymin: 34.82742 xmax: -78.49929 ymax: 35.50912
#> CRS:            4267
if (FALSE) {
  library(sp)
  example(meuse, ask = FALSE, echo = FALSE)
  try(st_write(st_as_sf(meuse), "PG:dbname=postgis", "meuse",
       layer_options = "OVERWRITE=true"))
  try(st_meuse <- st_read("PG:dbname=postgis", "meuse"))
  if (exists("st_meuse"))
    summary(st_meuse)
}

if (FALSE) {
## note that we need special escaping of layer  within single quotes (nc.gpkg)
## and that geom needs to be included in the select, otherwise we don't detect it
layer <- st_layers(system.file("gpkg/nc.gpkg", package = "sf"))$name[1]
nc_gpkg_sql = st_read(system.file("gpkg/nc.gpkg", package = "sf"),
   query = sprintf("SELECT NAME, SID74, FIPS, geom  FROM \"%s\" WHERE BIR74 > 20000", layer))
}
# spatial filter, as wkt:
wkt = st_as_text(st_geometry(nc[1,]))
# filter by (bbox overlaps of) first feature geometry:
read_sf(system.file("gpkg/nc.gpkg", package="sf"), wkt_filter = wkt)
#> Simple feature collection with 4 features and 14 fields
#> geometry type:  MULTIPOLYGON
#> dimension:      XY
#> bbox:           xmin: -81.91116 ymin: 35.98933 xmax: -80.87086 ymax: 36.58965
#> CRS:            4267
#> # A tibble: 4 x 15
#>    AREA PERIMETER CNTY_ CNTY_ID NAME  FIPS  FIPSNO CRESS_ID BIR74 SID74 NWBIR74
#>   <dbl>     <dbl> <dbl>   <dbl> <chr> <chr>  <dbl>    <int> <dbl> <dbl>   <dbl>
#> 1 0.081      1.29  1880    1880 Wata… 37189  37189       95  1323     1      17
#> 2 0.114      1.44  1825    1825 Ashe  37009  37009        5  1091     1      10
#> 3 0.199      1.98  1874    1874 Wilk… 37193  37193       97  3146     4     200
#> 4 0.061      1.23  1827    1827 Alle… 37005  37005        3   487     0      10
#> # … with 4 more variables: BIR79 <dbl>, SID79 <dbl>, NWBIR79 <dbl>,
#> #   geom <MULTIPOLYGON [°]>
# read geojson from string:
geojson_txt <- paste("{\"type\":\"MultiPoint\",\"coordinates\":",
   "[[3.2,4],[3,4.6],[3.8,4.4],[3.5,3.8],[3.4,3.6],[3.9,4.5]]}")
x = read_sf(geojson_txt)
x
#> Simple feature collection with 1 feature and 0 fields
#> geometry type:  MULTIPOINT
#> dimension:      XY
#> bbox:           xmin: 3 ymin: 3.6 xmax: 3.9 ymax: 4.6
#> CRS:            4326
#> # A tibble: 1 x 1
#>                                                         geometry
#>                                                 <MULTIPOINT [°]>
#> 1 ((3.2 4), (3 4.6), (3.8 4.4), (3.5 3.8), (3.4 3.6), (3.9 4.5))
if (FALSE) {
library(RPostgreSQL)
try(conn <- dbConnect(PostgreSQL(), dbname = "postgis"))
if (exists("conn") && !inherits(conn, "try-error")) {
  x = st_read(conn, "meuse", query = "select * from meuse limit 3;")
  x = st_read(conn, table = "public.meuse")
  print(st_crs(x)) # SRID resolved by the database, not by GDAL!
  dbDisconnect(conn)
 }
}