Simple geographical vector interaction built on top of ArchGDAL. Inspiration from geopandas.
Some basic examples without explanation follow here, for a complete overview, please check the documentation.
]add GeoDataFramesThere's no special type here. You just use normal DataFrames with a Vector of ArchGDAL geometries as a column.
import GeoDataFrames as GDF
df = GDF.read("test_points.shp")
10×2 DataFrame
Row │ geometry name
│ IGeometr… String
─────┼────────────────────────────
1 │ Geometry: wkbPoint test
2 │ Geometry: wkbPoint test
3 │ Geometry: wkbPoint test
4 │ Geometry: wkbPoint test
5 │ Geometry: wkbPoint test
6 │ Geometry: wkbPoint test
7 │ Geometry: wkbPoint test
8 │ Geometry: wkbPoint test
9 │ Geometry: wkbPoint test
10 │ Geometry: wkbPoint testYou can also specify the layer index or layer name in opening, useful if there are multiple layers:
GDF.read("test_points.shp", 0)
GDF.read("test_points.shp", "test_points")Any keywords arguments are passed on to the underlying ArchGDAL read function:
GDF.read("test.csv", options=["GEOM_POSSIBLE_NAMES=point,linestring", "KEEP_GEOM_COLUMNS=NO"])using DataFrames
coords = zip(rand(10), rand(10))
df = DataFrame(geometry=createpoint.(coords), name="test");
GDF.write("test_points.shp", df)You can also set options such as the layer_name, coordinate reference system, the driver and its options:
import GeoFormatTypes as GFT
GDF.write("test_points.shp", df; layer_name="data", crs=GFT.EPSG(4326), driver="FlatGeoBuf", options=Dict("SPATIAL_INDEX"=>"YES"))Note that any Tables.jl compatible table with GeoInterface.jl compatible geometries can be written by GeoDataFrames. You might want
to pass which column(s) contain geometries, or by defining GeoInterface.geometrycolumns on your table. Multiple geometry columns,
when enabled by the driver, can be provided in this way.
table = [(; geom=AG.createpoint(1.0, 2.0), name="test")]
GDF.write(tfn, table; geom_columns=(:geom,),)The supported operations are the ArchGDAL operations that are exported again to work on Vectors of geometries as well. Hence, if you can apply all the ArchGDAL operations yourself.
df.geom = buffer(df.geom, 10); # points turn into polygons
df
10×2 DataFrame
Row │ geometry name
│ IGeometr… String
─────┼──────────────────────────────
1 │ Geometry: wkbPolygon test
2 │ Geometry: wkbPolygon test
3 │ Geometry: wkbPolygon test
4 │ Geometry: wkbPolygon test
5 │ Geometry: wkbPolygon test
6 │ Geometry: wkbPolygon test
7 │ Geometry: wkbPolygon test
8 │ Geometry: wkbPolygon test
9 │ Geometry: wkbPolygon test
10 │ Geometry: wkbPolygon testimport GeoFormatTypes as GFT
df.geometry = reproject(df.geometry, GFT.EPSG(4326), GFT.EPSG(28992))
10-element Vector{ArchGDAL.IGeometry{ArchGDAL.wkbPolygon}}:
Geometry: POLYGON ((-472026.042542408 -4406233.59953401,-537 ... 401))
Geometry: POLYGON ((-417143.506054105 -4395423.99277048,-482 ... 048))
Geometry: POLYGON ((-450303.142569437 -4301418.89063867,-515 ... 867))
Geometry: POLYGON ((-434522.645535154 -4351075.81124634,-500 ... 634))
Geometry: POLYGON ((-443909.665585927 -4412565.43193349,-509 ... 349))
Geometry: POLYGON ((-438405.666500747 -4299366.23767677,-503 ... 677))
Geometry: POLYGON ((-400588.951193713 -4365333.532287,-46626 ... 287))
Geometry: POLYGON ((-409160.489179734 -4388484.98554538,-474 ... 538))
Geometry: POLYGON ((-453963.150526169 -4408927.89965336,-519 ... 336))
Geometry: POLYGON ((-498317.413693272 -4321687.31588764,-563 ... 764))using Plots
plot(df.geometry)