【822】GeoPandas 绘图

参考：Mapping and Plotting Tools

参考：geopandas.GeoDataFrame.plot

参考：Choosing Colormaps

参考：geopandas，用python分析地理空间数据原来这么简单！

1. 基本地图显示

import pandas as pd
import geopandas
import matplotlib.pyplot as plt
%matplotlib inline

world = geopandas.read_file(geopandas.datasets.get_path('naturalearth_lowres'))
# 加上末尾的分号，不会先是某行文字
world.plot(figsize=(20,10));

2. 显示地图边界线

world.boundary.plot(figsize=(20,10))

3. 专题地图显示

• 属性对应的列
• 选择地图的颜色模式
• 显示大小
• 边界颜色

# remove the record of Antarctica
world = world[(world.pop_est>0) & (world.name!="Antarctica")]
# add a new column "gdp_per_cap"
world['gdp_per_cap'] = world.gdp_md_est / world.pop_est
# show the world map based on "gdp_per_cap", different colors, with black edge
world.plot(column='gdp_per_cap', cmap='OrRd', figsize=(20,10), edgecolor="black");

4. 专题地图加入图例

# Plot population estimates with an accurate legend
import matplotlib.pyplot as plt

fig, ax = plt.subplots(1, 1, figsize=(20,12))

world.plot(column='gdp_per_cap',
           ax=ax,
           cmap='OrRd',
           edgecolor='black',
           legend=True,
           legend_kwds={'label': "GDP per capita by Country", 'orientation': "horizontal"});

fig, ax = plt.subplots(1, 1, figsize=(20,6))

world.plot(column='gdp_per_cap',
           ax=ax,
           cmap='OrRd',
           edgecolor='black',
           legend=True,
           legend_kwds={'label': "GDP per capita by Country", 'orientation': "vertical"});

5. 多图层显示

cities = geopandas.read_file(geopandas.datasets.get_path('naturalearth_cities'))

base = world.plot(color='#CCFFE5', edgecolor='black', figsize=(20,8))
cities.plot(ax=base, marker='o', color='red', markersize=10);