import geopandas as gpd

Indexing and Selecting Data 

world = gpd.read_file(gpd.datasets.get_path("naturalearth_lowres"))

type(world), world.shape

(geopandas.geodataframe.GeoDataFrame, (177, 6))
world.head()
pop_est continent name iso_a3 gdp_md_est geometry
0 920938 Oceania Fiji FJI 8374.0 MULTIPOLYGON (((180.00000 -16.06713, 180.00000...
1 53950935 Africa Tanzania TZA 150600.0 POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...
2 603253 Africa W. Sahara ESH 906.5 POLYGON ((-8.66559 27.65643, -8.66512 27.58948...
3 35623680 North America Canada CAN 1674000.0 MULTIPOLYGON (((-122.84000 49.00000, -122.9742...
4 326625791 North America United States of America USA 18560000.0 MULTIPOLYGON (((-122.84000 49.00000, -120.0000... 
world.continent.value_counts()

Africa                     51
Asia                       47
Europe                     39
North America              18
South America              13
Oceania                     7
Antarctica                  1
Seven seas (open ocean)     1
Name: continent, dtype: int64
world.crs

<Geographic 2D CRS: EPSG:4326>
Name: WGS 84
Axis Info [ellipsoidal]:
- Lat[north]: Geodetic latitude (degree)
- Lon[east]: Geodetic longitude (degree)
Area of Use:
- name: World.
- bounds: (-180.0, -90.0, 180.0, 90.0)
Datum: World Geodetic System 1984
- Ellipsoid: WGS 84
- Prime Meridian: Greenwich
southern_world = world.cx[:, :0]

southern_world.plot(figsize=(10,6))

<AxesSubplot:>
southern_world.crs

<Geographic 2D CRS: EPSG:4326>
Name: WGS 84
Axis Info [ellipsoidal]:
- Lat[north]: Geodetic latitude (degree)
- Lon[east]: Geodetic longitude (degree)
Area of Use:
- name: World.
- bounds: (-180.0, -90.0, 180.0, 90.0)
Datum: World Geodetic System 1984
- Ellipsoid: WGS 84
- Prime Meridian: Greenwich

Mapping 

world = gpd.read_file(gpd.datasets.get_path("naturalearth_lowres"))

cities = gpd.read_file(gpd.datasets.get_path("naturalearth_cities"))

world.head()
pop_est continent name iso_a3 gdp_md_est geometry
0 920938 Oceania Fiji FJI 8374.0 MULTIPOLYGON (((180.00000 -16.06713, 180.00000...
1 53950935 Africa Tanzania TZA 150600.0 POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...
2 603253 Africa W. Sahara ESH 906.5 POLYGON ((-8.66559 27.65643, -8.66512 27.58948...
3 35623680 North America Canada CAN 1674000.0 MULTIPOLYGON (((-122.84000 49.00000, -122.9742...
4 326625791 North America United States of America USA 18560000.0 MULTIPOLYGON (((-122.84000 49.00000, -120.0000... 
world.plot()

<AxesSubplot:>
cities.head()
name geometry
0 Vatican City POINT (12.45339 41.90328)
1 San Marino POINT (12.44177 43.93610)
2 Vaduz POINT (9.51667 47.13372)
3 Luxembourg POINT (6.13000 49.61166)
4 Palikir POINT (158.14997 6.91664) 
cities.plot()

<AxesSubplot:>
ax = world.plot()

cities.plot(ax=ax)

<AxesSubplot:>
<Figure size 432x288 with 0 Axes>

Choropleth Maps 

world = world[(world.pop_est>0) & (world.name!="Antarctica")]

world.shape

(176, 6)
world['gdp_per_cap'] = world.gdp_md_est/world.pop_est

world.plot(column="gdp_per_cap", figsize=(10,6))

<AxesSubplot:>

Creating a legend 

from mpl_toolkits.axes_grid1 import make_axes_locatable
fig, ax = plt.subplots(1, 1)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.1)
world.plot(column='pop_est', ax=ax, legend=True, cax=cax, figsize=(10,6))

<AxesSubplot:>
world.boundary.plot()

<AxesSubplot:>

Maps with Layers 

cities.plot(marker="*", color="green", markersize=5)

<AxesSubplot:>
cities.crs, world.crs

(<Geographic 2D CRS: EPSG:4326>
 Name: WGS 84
 Axis Info [ellipsoidal]:
 - Lat[north]: Geodetic latitude (degree)
 - Lon[east]: Geodetic longitude (degree)
 Area of Use:
 - name: World.
 - bounds: (-180.0, -90.0, 180.0, 90.0)
 Datum: World Geodetic System 1984
 - Ellipsoid: WGS 84
 - Prime Meridian: Greenwich,
 <Geographic 2D CRS: EPSG:4326>
 Name: WGS 84
 Axis Info [ellipsoidal]:
 - Lat[north]: Geodetic latitude (degree)
 - Lon[east]: Geodetic longitude (degree)
 Area of Use:
 - name: World.
 - bounds: (-180.0, -90.0, 180.0, 90.0)
 Datum: World Geodetic System 1984
 - Ellipsoid: WGS 84
 - Prime Meridian: Greenwich)
cities = cities.to_crs(world.crs)
Plot layers: option 1 
base = world.plot(color="white", edgecolor="black")
cities.plot(ax=base, marker="o", color="red", markersize=5)

<AxesSubplot:>
Plot layers: option 2 
import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.set_aspect("equal")
world.plot(ax=ax, color="white", edgecolor="black")
cities.plot(ax=ax, marker="o", color="red", markersize=5)
plt.show()