这篇文章主要讲解了“怎么用Python实现中国地图”，文中的讲解内容简单清晰，易于学习与理解，下面请大家跟着小编的思路慢慢深入，一起来研究和学习“怎么用Python实现中国地图”吧！
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代码如下：
import numpy as npimport matplotlib.pyplot as pltfrom mpl_toolkits.basemap import Basemapimport cmapsimport shapefilefrom matplotlib.path import Pathfrom matplotlib.patches import PathPatchny = grid_z.shape[0]nx = grid_z.shape[1]fig=plt.figure(figsize=(16,9))plt.rc('font',size=15,weight='bold')ax=fig.add_subplot(111)plt.title(u'd_rmse_tmax_012_24h',size=25,weight='bold')mp=Basemap(llcrnrlon=73.,llcrnrlat=15.,urcrnrlon=136.,urcrnrlat=55,projection='cyl')CHN='G:\\DATA\\MAP\\china-shapefiles-master\\'mp.readshapefile(CHN+'china','china',drawbounds=True)sf = shapefile.Reader(CHN+'china_country')for shape_rec in sf.shapeRecords():if shape_rec.record[8] == 'CHN':vertices = []codes = []pts = shape_rec.shape.pointsprt = list(shape_rec.shape.parts) + [len(pts)]for i in range(len(prt) - 1):for j in range(prt[i], prt[i+1]):vertices.append((pts[j][0], pts[j][1]))codes += [Path.MOVETO]codes += [Path.LINETO] * (prt[i+1] - prt[i] -2)codes += [Path.CLOSEPOLY]clip = Path(vertices, codes)clip = PathPatch(clip, transform=ax.transData)levels=np.linspace(-0.2,0.2,21)lons, lats = mp.makegrid(nx, ny) # get lat/lons of ny by nx evenly space grid.x, y = mp(lons, lats)cf=mp.contourf(x,y,grid_z,levels=levels,extend='both',cmap=cmaps.MPL_bwr)for contour in cf.collections:contour.set_clip_path(clip)cbar=mp.colorbar(cf,location='right',format='%8.2f',size=0.3,ticks=np.linspace(-0.2,0.2,11))left, bottom, width, height = 0.15, 0.63, 0.25, 0.25plt.axes([bottom, left, width, height])mf=Basemap(llcrnrlon=107.,llcrnrlat=2.,urcrnrlon=122.,urcrnrlat=22,projection='cyl')CHN='G:\\DATA\\MAP\\china-shapefiles-master\\'mf.readshapefile(CHN+'china','china',drawbounds=True)CHN='G:\\DATA\\MAP\\china-shapefiles-master\\'mf.readshapefile(CHN+'china_nine_dotted_line','china_nine_dotted_line',drawbounds=True,linewidth=1.5)mf.drawcoastlines()plt.show()
出图效果如下：
感谢各位的阅读，以上就是“怎么用Python实现中国地图”的内容了，经过本文的学习后，相信大家对怎么用Python实现中国地图这一问题有了更深刻的体会，具体使用情况还需要大家实践验证。这里是创新互联，小编将为大家推送更多相关知识点的文章，欢迎关注！
