I'm plotting world map-data at a country level, using the geometries provided in the Cartopy shapereader natural earth records:
import cartopy.io.shapereader as shpreader
import pandas as pd
my_data = pd.read_csv("my_data.csv", index_col = 0)
shpfilename = shpreader.natural_earth(resolution='50m',
category='cultural',
name='admin_0_countries')
reader = shpreader.Reader(shpfilename)
countries = reader.records()
for country in countries:
sovgt = country.attribute["SOVEREIGNT"]
plot_val = my_data.loc[sovgt]
ax.add_geometries([country.geometry],
ccrs.PlateCarree(),
facecolor = cmap(plot_val))
My question is: is there a neater way to extract data about a specific country from countries given that it is a generator. It would be highly preferable if I could do something like
for country in my_data.index.to_list():
geometry = countries[country].geometry
ax.add_geometries(geometry,
ccrs.PlateCarree(),
facecolor = cmap(plot_val))
The reason for this is that my index of countries in my_data does not align with the names of countries in countries. I have a tiered list of try:, except KeyError: with dicts of names to handle all the dependant states etc that aren't listed seperately in my dataset.
This is probably a more general question about generator objects. Apologies if it also a stupid question.
I don't have any insight for generators, but I answered a related question about colouring a nation on a map from a list of nation names and values https://stackoverflow.com/a/61525984/13208790
The key step is reading the natural earth data into geopandas, so you have a dataframe rather than a generator to work with. Not very elegant but should work:
import geopandas
from cartopy.io import shapereader
shpfilename = shapereader.natural_earth('50m', 'cultural', 'admin_0_countries')
df = geopandas.read_file(shpfilename)
df.head()