cartopy
cartopy is based on matplotlib, can visualize geo information combining with proj, numpy and shapely.
import cartopy.crs as ccrs
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter
import matplotlib.pyplot as plt
def main():
fig = plt.figure(figsize=(8, 10))
# Label axes of a Plate Carree projection with a central longitude of 180:
ax1 = fig.add_subplot(2, 1, 1,
projection=ccrs.PlateCarree(central_longitude=180))
ax1.set_global()
ax1.coastlines()
ax1.set_xticks([0, 60, 120, 180, 240, 300, 360], crs=ccrs.PlateCarree())
ax1.set_yticks([-90, -60, -30, 0, 30, 60, 90], crs=ccrs.PlateCarree())
lon_formatter = LongitudeFormatter(zero_direction_label=True)
lat_formatter = LatitudeFormatter()
ax1.xaxis.set_major_formatter(lon_formatter)
ax1.yaxis.set_major_formatter(lat_formatter)
plt.show()
if __name__ == '__main__':
main()
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import matplotlib.pyplot as plt
def main():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection=ccrs.PlateCarree())
ax.set_extent([-20, 60, -40, 45], crs=ccrs.PlateCarree())
ax.add_feature(cfeature.LAND)
ax.add_feature(cfeature.OCEAN)
ax.add_feature(cfeature.COASTLINE)
ax.add_feature(cfeature.BORDERS, linestyle=':')
ax.add_feature(cfeature.LAKES, alpha=0.5)
ax.add_feature(cfeature.RIVERS)
plt.show()
if __name__ == '__main__':
main()
geopandas
geopandas is mainly used to process geo data, it can also visualize geo data with help of matplotlib.
import geopandas as gpd
from matplotlib_scalebar.scalebar import ScaleBar
nybb = gpd.read_file(gpd.datasets.get_path('nybb'))
nybb = nybb.to_crs(32619) # Convert the dataset to a coordinate
# system which uses meters
ax = nybb.plot()
ax.add_artist(ScaleBar(1))
import geopandas
import contextily as cx
df = geopandas.read_file(geopandas.datasets.get_path('nybb'))
ax = df.plot(figsize=(10, 10), alpha=0.5, edgecolor='k')
df.crs
df_wm = df.to_crs(epsg=3857)
ax = df_wm.plot(figsize=(10, 10), alpha=0.5, edgecolor='k')
cx.add_basemap(ax)
