Geopandas & Mapplotlib, how do I plot without an o

When I run the code below in a Jupyter Notebook, I get a map of the world, colored in red.

There are fine white-ish lines between the countries. Is there a way to plot the world so that all countries are solid and there's no line in between?

I'm asking, because my real world usecase is a fine grid that behaves just like the world map: Each grid shape has a fine outline which I do not want to have in the plot. (Update, since this was asked: The grid shapes will not have the same fill color.

)

import geopandas as gpd
import geoplot as gplt
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
world['total'] = 1
world.plot(column='total', cmap='Set1')

For the grid example, the grid files are at https://opendata-esri-de.opendata.arcgis.com/datasets/3c1f46241cbb4b669e18b002e4893711_0 A simplified example that shows the problem.

sf = 'Hexagone_125_km/Hexagone_125_km.shp'
shp = gpd.read_file(sf)
shp.crs = {'init': 'epsg:4326'}
shp['sum'] = 1  # for example, fill sum with something
shp.plot(figsize=(20,20), column='sum', cmap='gnuplot', alpha=1, legend=True)

The white lines are due to antialiasing. This usually makes the visual more smooth, but leads to white lines in between different shapes. You can turn off anialiasing via

antialiased=False

That has the inevitable drawback of the plot looking pixelated.

An alternative is to give the patches an edge with a certain linewidth. The edges should probably have the same color as the faces, so

edgecolor="face", linewidth=0.4

would be an option. This removes the white lines, but introduces a slight "searing" effect (You'll notice mainly looking at islands like Indonesia or Japan). This will be the more noticable, the smaller the features, so it may be irrelevant for showing a hexbin plot. Still, playing a bit with the linewidth might improve the result further.

Code for reproduction:

import numpy as np; np.random.seed(42)
import geopandas as gpd
import matplotlib.pyplot as plt

world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
world['total'] = np.random.randint(0,10, size=len(world))

fig, (ax1, ax2, ax3) = plt.subplots(nrows=3, figsize=(7,10))

world.plot(column='total', cmap='Set1', ax=ax1)

world.plot(column='total', cmap='Set1', ax=ax2, antialiased=False)

world.plot(column='total', cmap='Set1', ax=ax3, edgecolor="face", linewidth=0.4)


ax1.set_title("original")
ax2.set_title("antialiased=False")
ax3.set_title("edgecolor='face', linewidth=0.4")
plt.tight_layout()
plt.savefig("world.png")
plt.show()