I'm working with geospacial data and I have two pandas dataframes with two different regions, both have a column geometry
with the (multi)polygons and a column SCORE
with a value for each of the (multi)polygons I want to plot.
For example, this is the plot for the provinces of Spain excluding Canary Islands:
shapefile_prov.plot(column="SCORE", legend=True)
plt.xticks([])
plt.yticks([])
And this is the plot of the dataframe with Canary Island:
shapefile_prov_can.plot(column="SCORE", legend=True)
plt.xticks([])
plt.yticks([])
Is there a way to colour the graph for Canary Islands with the same scale of colours of the first graph? What I mean is that yellow colour should be associated to values of SCORE
roughly above 0.5 and purple for values below 0.325 approximately.
A quick/simple option would be to agg
the min
/max
of scores and pass it to the plot
:
cmap_range = shapefile_prov["SCORE"].agg({"vmin": "min", "vmax": "max"})
shapefile_prov_can.plot(column="SCORE", legend=True, **cmap_range)
NB: The plot below uses an AxesDivider to improve the appearance of the colorbar.