I would like to know how to change the legend automatically generated by Geopandas. Mostly I would like to reduce its size because it's quite big on the generated image. The legend seems to take all the available space.
Additional question, do you know how to remove the empty space below my map ? I've tried with
pad_inches = 0, bbox_inches='tight'
but I still have an empty space below the map.
Thanks for your help.
This works for me:
some_geodataframe.plot(..., legend=True, legend_kwds={'shrink': 0.3})
Other options here: https://matplotlib.org/api/_as_gen/matplotlib.pyplot.colorbar.html
To show how to get proper size of a colorbar legend accompanying a map created by geopandas' plot() method I use the built-in 'naturalearth_lowres' dataset.
The working code is as follows.
import matplotlib.pyplot as plt
import geopandas as gpd
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
world = world[(world.name != "Antarctica") & (world.name != "Fr. S. Antarctic Lands")] # exclude 2 no-man lands
plot as usual, grab the axes 'ax' returned by the plot
colormap = "copper_r" # add _r to reverse the colormap
ax = world.plot(column='pop_est', cmap=colormap, \
figsize=[12,9], \
vmin=min(world.pop_est), vmax=max(world.pop_est))
map marginal/face deco
ax.set_title('World Population')
ax.grid()
colorbar will be created by ...
fig = ax.get_figure()
# add colorbar axes to the figure
# here, need trial-and-error to get [l,b,w,h] right
# l:left, b:bottom, w:width, h:height; in normalized unit (0-1)
cbax = fig.add_axes([0.95, 0.3, 0.03, 0.39])
cbax.set_title('Population')
sm = plt.cm.ScalarMappable(cmap=colormap, \
norm=plt.Normalize(vmin=min(world.pop_est), vmax=max(world.pop_est)))
at this stage, 'cbax' is just a blank axes, with un needed labels on x and y axes blank-out the array of the scalar mappable 'sm'
sm._A = []
draw colorbar into 'cbax'
fig.colorbar(sm, cax=cbax, format="%d")
# dont use: plt.tight_layout()
plt.show()
Read the comments in the code for useful info.
The resulting plot:
