Reading and Writing Files¶
Reading Spatial Data¶
geopandas can read almost any vector-based spatial data format including ESRI shapefile, GeoJSON files and more using the command:
which returns a GeoDataFrame object. (This is possible because geopandas makes use of the great fiona library, which in turn makes use of a massive open-source program called GDAL/OGR designed to facilitate spatial data transformations).
Any arguments passed to
read_file() after the file name will be passed directly to
fiona.open, which does the actual data importation. In general,
read_file is pretty smart and should do what you want without extra arguments, but for more help, type:
import fiona; help(fiona.open)
Among other things, one can explicitly set the driver (shapefile, GeoJSON) with the
driver keyword, or pick a single layer from a multi-layered file with the
countries_gdf = geopandas.read_file("package.gpkg", layer='countries')
Where supported in
fiona, geopandas can also load resources directly from
a web URL, for example for GeoJSON files from geojson.xyz:
url = "http://d2ad6b4ur7yvpq.cloudfront.net/naturalearth-3.3.0/ne_110m_land.geojson" df = geopandas.read_file(url)
You can also load ZIP files that contain your data:
zipfile = "zip:///Users/name/Downloads/cb_2017_us_state_500k.zip" states = geopandas.read_file(zipfile)
If the dataset is in a folder in the ZIP file, you have to append its name:
zipfile = "zip:///Users/name/Downloads/gadm36_AFG_shp.zip!data"
If there are multiple datasets in a folder in the ZIP file, you also have to specify the filename:
zipfile = "zip:///Users/name/Downloads/gadm36_AFG_shp.zip!data/gadm36_AFG_1.shp"
geopandas can also get data from a PostGIS database using the
Writing Spatial Data¶
GeoDataFrames can be exported to many different standard formats using the
GeoDataFrame.to_file() method. For a full list of supported formats, type
import fiona; fiona.supported_drivers.
Writing to Shapefile:
Writing to GeoJSON:
Writing to GeoPackage:
countries_gdf.to_file("package.gpkg", layer='countries', driver="GPKG") cities_gdf.to_file("package.gpkg", layer='cities', driver="GPKG")