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glimpse() is like a transposed version of print(): layers/columns run down the page, and data runs across. This makes it possible to see every layer/column in a Spat* object.

Usage

# S3 method for class 'SpatRaster'
glimpse(x, width = NULL, ..., n = 10, max_extra_cols = 20)

# S3 method for class 'SpatVector'
glimpse(x, width = NULL, ..., n = 10, max_extra_cols = 20)

Arguments

x

A SpatRaster created with terra::rast() or a SpatVector created with terra::vect().

width

Width of output: defaults to the setting of the width option (if finite) or the width of the console. See dplyr::glimpse().

...

Arguments passed on to as_tibble() methods for SpatRaster and SpatVector. See as_tibble.SpatRaster().

n

Maximum number of rows to show.

max_extra_cols

Number of extra columns or layers to print abbreviated information for, if n is too small for the Spat* object.

Value

original x is (invisibly) returned, allowing glimpse() to be used within a data pipeline.

terra equivalent

print()

Methods

Implementation of the generic dplyr::glimpse() function for Spat*. objects.

Examples


library(terra)

# SpatVector
v <- vect(system.file("extdata/cyl.gpkg", package = "tidyterra"))

v %>% glimpse(n = 2)
#> #  A SpatVector 9 x 3
#> #  Geometry type: Polygons
#> #  Projected CRS: ETRS89-extended / LAEA Europe (EPSG:3035)
#> #  CRS projection units: meter <m>
#> #  Extent (x / y) : ([2,892,687 / 3,341,372] , [2,017,622 / 2,361,600])
#> 
#> $ iso2 <chr> "ES-AV", "ES-BU", "ES-LE", "ES-P", "ES-SA", "ES-SG", "ES-SO", "ES…
#> $ cpro <chr> "05", "09", "24", "34", "37", "40", "42", "47", "49"
#> # ℹ 1 more variable : name <chr>
#> # ℹ Use `tidyterra::glimpse(n = ...)` to see more columns

# Use on a pipeline
v %>%
  glimpse() %>%
  mutate(a = 30) %>%
  # with options
  glimpse(geom = "WKT")
#> #  A SpatVector 9 x 3
#> #  Geometry type: Polygons
#> #  Projected CRS: ETRS89-extended / LAEA Europe (EPSG:3035)
#> #  CRS projection units: meter <m>
#> #  Extent (x / y) : ([2,892,687 / 3,341,372] , [2,017,622 / 2,361,600])
#> 
#> $ iso2 <chr> "ES-AV", "ES-BU", "ES-LE", "ES-P", "ES-SA", "ES-SG", "ES-SO", "ES…
#> $ cpro <chr> "05", "09", "24", "34", "37", "40", "42", "47", "49"
#> $ name <chr> "Avila", "Burgos", "Leon", "Palencia", "Salamanca", "Segovia", "S…
#> #  A SpatVector 9 x 4
#> #  Geometry type: Polygons
#> #  Projected CRS: ETRS89-extended / LAEA Europe (EPSG:3035)
#> #  CRS projection units: meter <m>
#> #  Extent (x / y) : ([2,892,687 / 3,341,372] , [2,017,622 / 2,361,600])
#> 
#> $ iso2     <chr> "ES-AV", "ES-BU", "ES-LE", "ES-P", "ES-SA", "ES-SG", "ES-SO",…
#> $ cpro     <chr> "05", "09", "24", "34", "37", "40", "42", "47", "49"
#> $ name     <chr> "Avila", "Burgos", "Leon", "Palencia", "Salamanca", "Segovia"…
#> $ a        <dbl> 30, 30, 30, 30, 30, 30, 30, 30, 30
#> $ geometry <chr> "POLYGON ((3126360.2417 2066777.7545, 3125073.9752 2065007.29…

# SpatRaster
r <- rast(system.file("extdata/cyl_elev.tif", package = "tidyterra"))

r %>% glimpse()
#> #  A SpatRaster 126 x 212 x 1 layer (26,712 cells)
#> #  Resolution (x / y): (1' 30" , 1' 30")
#> #  Geodetic CRS: lon/lat WGS 84 (EPSG:4326)
#> #  Extent (x / y) : ([7° 4' 30" W / 1° 46' 30" W] , [40° 4' 60" N / 43° 13' 60" N])
#> 
#> $ elevation_m <dbl> 700.2969, 780.3889, 706.1250, 568.9722, 584.9028, 506.7361…

# Use on a pipeline
r %>%
  glimpse() %>%
  mutate(b = elevation_m / 100) %>%
  # With options
  glimpse(xy = TRUE)
#> #  A SpatRaster 126 x 212 x 1 layer (26,712 cells)
#> #  Resolution (x / y): (1' 30" , 1' 30")
#> #  Geodetic CRS: lon/lat WGS 84 (EPSG:4326)
#> #  Extent (x / y) : ([7° 4' 30" W / 1° 46' 30" W] , [40° 4' 60" N / 43° 13' 60" N])
#> 
#> $ elevation_m <dbl> 700.2969, 780.3889, 706.1250, 568.9722, 584.9028, 506.7361…
#> #  A SpatRaster 126 x 212 x 2 layers (26,712 cells)
#> #  Resolution (x / y): (1' 30" , 1' 30")
#> #  Geodetic CRS: lon/lat WGS 84 (EPSG:4326)
#> #  Extent (x / y) : ([7° 4' 30" W / 1° 46' 30" W] , [40° 4' 60" N / 43° 13' 60" N])
#> 
#> $ elevation_m <dbl> 700.2969, 780.3889, 706.1250, 568.9722, 584.9028, 506.7361…
#> $ b           <dbl> 7.002969, 7.803889, 7.061250, 5.689722, 5.849028, 5.067361…