CODEWITHSUNDEEP
rshapefiler-sf
Derek Corcoran
Derek Corcoran

Reputation: 4082

Read only the first line of a shapefile using SF in r

I am building a function to generate metadata for shapefiles in R.

One of my ideas was to get the name and class of each column in an SF (in case there is a massive SF and you don't have to wait to read all the data to get the names of them), for that I was looking into the read_sf function, specifically to at the query argument.

Following the example from this link, I saw that you can filter by the values of a column to get a smaller dataset for example:

library(sf)

nc = st_read(system.file("shape/nc.shp", package="sf"))

If I know the name of the columns beforehand I could filter with something like this:

nc_sql = st_read(system.file("shape/nc.shp", package="sf"),
                 query = "SELECT NAME, SID74, FIPS FROM \"nc\" WHERE BIR74 > 20000")

But of course the goal is to get the column names, so I would like to use something similar to what I see in this answer.

I have tried this code among other unsuccessful tries:

nc_sql = st_read(system.file("shape/nc.shp", package="sf"),
                 query = "SELECT TOP 1 * FROM \"nc\"")

Any help would be greatly apprecieated

Upvotes: 1

Views: 947

Answers (2)

Calleros
Calleros

Reputation: 128

You can pass a SQL query with read_sf. It should look like this

library(sf)    

data = read_sf('file.gpkg', query = 'SELECT * from layername LIMIT 1')

Upvotes: 1

Grzegorz Sapijaszko
Grzegorz Sapijaszko

Reputation: 3604

Use rgdal::ogrInfo

ogrInfo(system.file("shape/nc.shp", package="sf"))

and the result:

Source: "/home/sapi/R/x86_64-pc-linux-gnu-library/4.1/sf/shape/nc.shp", layer: "nc"
Driver: ESRI Shapefile; number of rows: 100 
Feature type: wkbPolygon with 2 dimensions
Extent: (-84.32385 33.88199) - (-75.45698 36.58965)
CRS: +proj=longlat +datum=NAD27 +no_defs 
LDID: 87 
Number of fields: 14 
        name type length typeName
1       AREA    2     24     Real
2  PERIMETER    2     24     Real
3      CNTY_    2     24     Real
4    CNTY_ID    2     24     Real
5       NAME    4     80   String
6       FIPS    4     80   String
7     FIPSNO    2     24     Real
8   CRESS_ID    0      9  Integer
9      BIR74    2     24     Real
10     SID74    2     24     Real
11   NWBIR74    2     24     Real
12     BIR79    2     24     Real
13     SID79    2     24     Real
14   NWBIR79    2     24     Real

Upvotes: 2

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