As written in the geopandas.datasets.get_path(...)
documentation, one has to execute
>>> geopandas.datasets.available
['naturalearth_lowres', 'naturalearth_cities', 'nybb']
Where
- naturalearth_lowres: contours of countries
- naturalearth_cities: positions of cities
- nybb: maybe New York?
Other data sources
Searching for “germany shapefile” gave an arcgis.com url which used the “Bundesamt für Kartographie und Geodäsie” as a source. The result of using vg2500_geo84/vg2500_krs.shp
looks like this:
Source:
© Bundesamt für Kartographie und Geodäsie, Frankfurt am Main, 2011
Vervielfältigung, Verbreitung und öffentliche Zugänglichmachung, auch auszugsweise, mit Quellenangabe gestattet.
I also had to set base.set_aspect(1.4)
, otherwise it looked wrong. The value 1.4
was found by trial and error.
Another source for such data for Berlin is daten.berlin.de
When geopandas reads the shapefile, it is a geopandas dataframe with the columns
['USE', 'RS', 'RS_ALT', 'GEN', 'SHAPE_LENG', 'SHAPE_AREA', 'geometry']
with:
USE=4
for all elementsRS
is a string like 16077 or 01003RS_ALT
is a string like 160770000000 or 010030000000GEN
is a string like'Saale-Holzland-Kreis'
or'Erlangen'
SHAPE_LENG
is a float like202986.1998816
or248309.91235015
SHAPE_AREA
is a float like1.91013141e+08
or1.47727769e+09
geometry
is a shapely geometry – mostly POLYGON