Fill countries in python basemap

As has already been said by @unutbu, Thomas' post here is exactly what you are after.

Should you want to do this with Cartopy, the corresponding code (in v0.7) can be adapted from http://scitools.org.uk/cartopy/docs/latest/tutorials/using_the_shapereader.html slightly:

import cartopy.crs as ccrsimport matplotlib.pyplot as pltimport cartopy.io.shapereader as shpreaderimport itertoolsimport numpy as npshapename = 'admin_0_countries'countries_shp = shpreader.natural_earth(resolution='110m',                                        category='cultural', name=shapename)# some nice "earthy" colorsearth_colors = np.array([(199, 233, 192),                                (161, 217, 155),                                (116, 196, 118),                                (65, 171, 93),                                (35, 139, 69),                                ]) / 255.earth_colors = itertools.cycle(earth_colors)ax = plt.axes(projection=ccrs.PlateCarree())for country in shpreader.Reader(countries_shp).records():    print country.attributes['name_long'], earth_colors.next()    ax.add_geometries(country.geometry, ccrs.PlateCarree(),                      facecolor=earth_colors.next(),                      label=country.attributes['name_long'])plt.show()

Inspired by the answer from pelson, I post the solution I have. I will leave it up to you which works best, so I will not accept any answer at the moment.

#! /usr/bin/env pythonimport sysimport osfrom pylab import *from mpl_toolkits.basemap import Basemapimport matplotlib as mpfrom shapelib import ShapeFileimport dbflibfrom matplotlib.collections import LineCollectionfrom matplotlib import cmdef get_shapeData(shp,dbf):  for npoly in range(shp.info()[0]):    shpsegs = []    shpinfo = []    shp_object = shp.read_object(npoly)    verts = shp_object.vertices()    rings = len(verts)    for ring in range(rings):        if ring == 0:            shapedict = dbf.read_record(npoly)        name = shapedict["name_long"]        continent = shapedict["continent"]        lons, lats = zip(*verts[ring])        if max(lons) > 721. or min(lons) < -721. or max(lats) > 91. or min(lats) < -91:            raise ValueError,msg        x, y = m(lons, lats)        shpsegs.append(zip(x,y))        shapedict['RINGNUM'] = ring+1        shapedict['SHAPENUM'] = npoly+1        shpinfo.append(shapedict)    lines = LineCollection(shpsegs,antialiaseds=(1,))    lines.set_facecolors(cm.jet(np.random.rand(1)))    lines.set_edgecolors('k')    lines.set_linewidth(0.3)    ax.add_collection(lines)if __name__=='__main__':  f=figure(figsize=(10,10))  ax = plt.subplot(111)  m = Basemap(projection='merc',llcrnrlat=30,urcrnrlat=72,\            llcrnrlon=-40,urcrnrlon=50,resolution='c')  m.drawcountries(linewidth=0.1,color='w')  sfile = 'ne_10m_admin_0_countries'  shp = ShapeFile(sfile)  dbf = dbflib.open(sfile)  get_shapeData(shp,dbf)  show()  sys.exit(0)

This is the result

Here is my example how to fill in Albania in the correct colour (not very elegant I know ;)).

  #HACK for Albania  shpsegs = []  shpinfo = []  shp_object = shp.read_object(9)  verts = shp_object.vertices()  rings = len(verts)  for ring in range(rings):      if ring == 0:          shapedict = dbf.read_record(9)      name = shapedict["name_long"]      continent = shapedict["continent"]      lons, lats = zip(*verts[ring])      if max(lons) > 721. or min(lons) < -721. or max(lats) > 91. or min(lats) < -91:          raise ValueError,msg      x, y = m(lons, lats)      shpsegs.append(zip(x,y))      shapedict['RINGNUM'] = ring+1      shapedict['SHAPENUM'] = npoly+1      shpinfo.append(shapedict)  lines = LineCollection(shpsegs,antialiaseds=(1,))  if name == 'Albania':    lines.set_facecolors('w')  lines.set_edgecolors('k')  lines.set_linewidth(0.3)  ax.add_collection(lines)

It is important that you do this after you have done all the other shapes. Perhaps you can get rid of some part of this code, but as I said it was sufficient for me.

For my application I coloured contries by name or continent, therefore these lines:

    name = shapedict["name_long"]    continent = shapedict["continent"]

The data used I got from this website: http://www.naturalearthdata.com/

Updating @pelson answer for Python 3:

import cartopy.crs as ccrsimport matplotlib.pyplot as pltimport cartopy.io.shapereader as shpreaderimport itertoolsimport numpy as npshapename = 'admin_0_countries'countries_shp = shpreader.natural_earth(resolution='110m',                                        category='cultural', name=shapename)print(countries_shp)# some nice "earthy" colorsearth_colors = np.array([(199, 233, 192),                         (161, 217, 155),                         (116, 196, 118),                         (65, 171, 93),                         (35, 139, 69),                        ]) / 255earth_colors = itertools.cycle(earth_colors)ax = plt.axes(projection=ccrs.PlateCarree())for country in shpreader.Reader(countries_shp).records():    print(country.attributes['NAME_LONG'], next(earth_colors))    ax.add_geometries(country.geometry, ccrs.PlateCarree(),                      facecolor=next(earth_colors),                      label=country.attributes['NAME_LONG'])plt.show()