geopandas中城市的多色

Question

我可以使用 geopandas 读取形状文件，但我想用一个州的不同颜色为不同的城市着色，我如何为一个州的不同城市着色不同的颜色？ 谢谢你。

        import geopandas as gpd

       gf_states = gpd.read_file('IND_adm2.shp')
gr_states.head()
    ID_0    ISO     NAME_0  ID_1    NAME_1  ID_2    NAME_2  TYPE_2  ENGTYPE_2   NL_NAME_2   VARNAME_2   geometry
0   105     IND     India   1   Andaman and Nicobar     1   Andaman Islands     District    District    None    None    MULTIPOLYGON (((93.64841 14.93487, 93.64917 14...
1   105     IND     India   1   Andaman and Nicobar     2   Nicobar Islands     District    District    None    None    MULTIPOLYGON (((92.78778 9.24417, 92.78889 9.2...
2   105     IND     India   2   Andhra Pradesh  3   Anantapur   District    District    None    Anantpur, Ananthapur    POLYGON ((77.69000 15.17628, 77.69378 15.17347...
3   105     IND     India   2   Andhra Pradesh  4   Chittoor    District    District    None    Chitoor|Chittor     POLYGON ((78.47611 13.93680, 78.48208 13.93007...
4   105     IND     India   2   Andhra Pradesh  5   Cuddapah    District    District    None    None    POLYGON ((78.94612 15.19465, 78.95062 15.18535...

---

这里假设我想为 NAME_2 着色（Anantapur 为红色，chittor 为蓝色，cuddapah 为黄色等一个州 NAME_1 Andhra Pradesh）。我怎么能这样做？ 谢谢。 我正在处理的代码如下：-

def fig_beauty_hires(ax,xlim=[66,78],ylim=[20,24],st_name,states=False,states_name=False):


import cartopy as crs
import cartopy.crs as ccrs
import cartopy.feature as cfeature
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
import geopandas as gpd

gf_states = gpd.read_file('IND_adm2.shp')
gdff = gf_states.loc[gf_states['NAME_1']==st_name,['geometry','NAME_2']]

if states_name:
    gf_new = gdff.cx[xlim[0]:xlim[1],ylim[0]:ylim[1]]
    state_points = gf_new.geometry.apply(lambda x :x.representative_point().coords[:])
    state_coords = [point[0] for point in state_points]

    cMap = ['#00FF00','#FFFF00','#00FFFF','#FF00FF','#FF4500','#7B68EE','#ADFF2F']
    for name, coord , col,j in zip(gf_new.NAME_2,state_coords,cMap,range(0,len(cMap))):
        #print(name)
        #ax.add_geometries(gdff.geometry,crs=ccrs.PlateCarree(),color=cMap[j],edgecolor='k')

        if name=="Nashik" or name=="Aurangabad"or name=="Jalna" or name=="Osmanabad"or name=="Gadag"or name=="Bellary"or                            name=="Mysore" or name=="Davanagere" or name=="Hassan" or name=="Greater Bombay"or name=="Thiruvananthapuram"or                          name=="Alappuzha" or name=="Kollam" or name=="Pattanamtitta" or name=="Idukki" or name=="Palakkad":
            print("if j:",str(cMap[j]))
            ax.add_geometries(gdff.geometry,crs=ccrs.PlateCarree(),facecolor=cMap[j],edgecolor='k')
            ax.text(x=coord[0],y=coord[1],s=" ",horizontalalignment='center',fontweight='normal',fontsize=10,color='k')

        else:
            print("else j:",str(cMap[j]))
            ax.add_geometries(gdff.geometry,crs=ccrs.PlateCarree(),facecolor=cMap[j],edgecolor='k')
            ax.text(x=coord[0],y=coord[1],s=name,horizontalalignment='center',fontweight='bold',fontsize=10,color='k')
if __name__=="__main__":
    import cartopy.crs as ccrs
    import cartopy.feature as cfeature

    from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER                

    fig, ax = plt.subplots(figsize=(19.20,10.80), subplot_kw={'projection': ccrs.PlateCarree()})  
    fig_beauty_hires(ax=ax)

Answer 1

目前还不完全清楚，您期望的最终输出是什么。而且您发布的代码无法运行（即使我们忽略了多个导入等）。

我的理解是，您想要绘制一些几何图形，以便能够控制每个几何图形的 facecolor。这是一个简单的 sn-p，您可以在此基础上进行构建：（我设法找到了一个与您发布的数据集相匹配的数据集。）

import geopandas as gpd
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
from cartopy.feature import ShapelyFeature

# Obtain the data & keep only relevant attributes
states = gpd.read_file('gadm36_IND.gpkg', layer=1)[['NAME_1', 'NAME_2', 'geometry']]

# Prepare the data for easy manipulations later
df = states[states.NAME_1 == 'Andhra Pradesh']
df.reset_index(inplace=True, drop=True) #for later convenience

# Prepare the projections
data_crs = ccrs.PlateCarree() # this will be fixed by your data
proj_crs = ccrs.PlateCarree() # this determines the projection of the plot
extents = [75, 86, 12, 20] # change as needed depending on the data

# Produce the main figure and axis
fig = plt.figure(figsize=(15, 15))
ax = fig.add_subplot(projection=proj_crs)

# Some configuration
ax.set_extent(extents, crs=data_crs)
ax.coastlines() # just for (some) spatial reference only

# Plot the geometries. A very basic plotting scheme shown here
colours = ['red', 'green', 'yellow'] # (almost) randomly selected
for index, row in df.iterrows():
    sp = ShapelyFeature(row.geometry, data_crs,
                        edgecolor='k', linewidth=0.5,
                        facecolor=colours[index%len(colours)])
    ax.add_feature(sp)
    locxy = row.geometry.representative_point()
    ax.annotate(row.NAME_2, xy=(locxy.x, locxy.y)) # use transform for other projections

plt.show()

The resulting plot