This notebook demonstrates the use of vector data provided via WFS. For instructions on using WMS, see the webmapping notebook.
For more information on open government data in Vienna visit digitales.wien.gv.at
For a full list of available datasets go to data.gv.at
import hvplot.pandas
from utils.dataaccess import get_gdf_from_wfs
from utils.plotting import hvplot_with_buffer
from holoviews import opts
opts.defaults(opts.Overlay(active_tools=['wheel_zoom'], frame_width=500, frame_height=400))
For example, transport bicycle sharing stations:
gdf = get_gdf_from_wfs('RADGRAETZELOGD')
gdf.hvplot(geo=True, tiles='OSM', hover_cols='all')
300 meters is often cited as the maximum walking distance to a bicycle sharing station.
hvplot_with_buffer(gdf, 300)
gdf2 = get_gdf_from_wfs('ELADESTELLEOGD')
By comparision, the network of EV charging stations is much more comprehensive:
hvplot_with_buffer(gdf, 100, title='Bike Sharing Stations') + hvplot_with_buffer(gdf2, 100, title='EV Charging Stations')
election_districts = get_gdf_from_wfs('WAHLSPRGR2020OGD')
election_districts.hvplot(geo=True, tiles='OSM', alpha=0.5)