MatPlotLib + GeoPandas：绘制多个图层，控制图形

Question

考虑到可用的形状文件here：我知道可以生成我需要的县级标签以及地图上某些点（如下所示）所需的基本地图。我遇到的问题是我似乎无法用figsize控制图形的大小。 这是我有：

import geopandas as gpd 
import matplotlib.pyplot as plt 
%matplotlib inline 
figsize=5,5 
fig = plt.figure(figsize=(figsize),dpi=300) 

shpfileshpfile=r'Y:\HQ\TH\Groups\NR\PSPD\Input\US_Counties\cb_2015_us_county_20m.shp' 
c=gpd.read_file(shpfile) 
c=c.loc[c['GEOID'].isin(['26161','26093','26049','26091','26075','26125','26163','26099','26115','26065'])] 
c['coords'] = c['geometry'].apply(lambda x: x.representative_point().coords[:]) 
c['coords'] = [coords[0] for coords in c['coords']] 
ax=c.plot() 

#Control some attributes regarding the axis (for the plot above) 

ax.spines['top'].set_visible(False);ax.spines['bottom'].set_visible(False);ax.spines['left'].set_visible(False);ax.spines['right'].set_visible(False) 
    ax.tick_params(axis='y',which='both',left='off',right='off',color='none',labelcolor='none') 
    ax.tick_params(axis='x',which='both',top='off',bottom='off',color='none',labelcolor='none') 
    for idx, row in c.iterrows(): 
     ax.annotate(s=row['NAME'], xy=row['coords'], 
        horizontalalignment='center') 
lat2=[42.5,42.3] 
lon2=[-84,-83.5] 

    #Add another plot... 

ax.plot(lon2,lat2,alpha=1,marker='o',linestyle='none',markeredgecolor='none',markersize=15,color='white') 
plt.show() 

正如你可以看到，我选择调用由轴名称情节，因为我需要控制轴的属性，如tick_params。我不确定是否有更好的方法。这看起来像一个“无脑”，但我似乎无法弄清楚为什么我无法控制数字大小。

提前致谢！

Answer 1

我必须做到以下几点：

1. 使用fig, ax = plt.subplots(1, 1, figsize = (figsize))

2.使用在c.plot斧头= A（）的参数

import geopandas as gpd 
import matplotlib.pyplot as plt 
%matplotlib inline 
figsize=5,5 
#fig = plt.figure(figsize=(figsize),dpi=300) 
#ax = fig.add_subplot(111) 
fig, ax = plt.subplots(1, 1, figsize = (figsize)) 
shpfileshpfile=r'Y:\HQ\TH\Groups\NR\PSPD\Input\US_Counties\cb_2015_us_county_20m.shp' 
c=gpd.read_file(shpfile) 
c=c.loc[c['GEOID'].isin(['26161','26093','26049','26091','26075','26125','26163','26099','26115','26065'])] 
c['coords'] = c['geometry'].apply(lambda x: x.representative_point().coords[:]) 
c['coords'] = [coords[0] for coords in c['coords']] 
c.plot(ax=ax) 
ax.spines['top'].set_visible(False);ax.spines['bottom'].set_visible(False);ax.spines['left'].set_visible(False);ax.spines['right'].set_visible(False) 
ax.tick_params(axis='y',which='both',left='off',right='off',color='none',labelcolor='none') 
ax.tick_params(axis='x',which='both',top='off',bottom='off',color='none',labelcolor='none') 
for idx, row in c.iterrows(): 
    ax.annotate(s=row['NAME'], xy=row['coords'], 
       horizontalalignment='center') 
lat2=[42.5,42.3] 
lon2=[-84,-83.5] 
ax.plot(lon2,lat2,alpha=1,marker='o',linestyle='none',markeredgecolor='none',markersize=15,color='white')