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Using GeoPandas for Geospatial Analysis in Python

Solution: Aggregation and Constructive Methods

Explore aggregation and constructive techniques in GeoPandas for geospatial analysis. Understand how to dissolve polygons to create continent boundaries, use buffers to define spatial limits, clip geospatial data, and calculate population density with region aggregation. Gain practical skills to enhance your ability to analyze and visualize spatial relationships using GeoPandas.

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Solution: Shore islands

Let's review the code solution:

Python 3.10.4
import geopandas as gpd
# open the datasets
islands = gpd.read_file('minor_islands.geojson')
countries = gpd.read_file('countries.geojson')
# create the continents boundaries
continents = countries.dissolve(by='continent')
# select the African continent
africa = continents.loc[['Africa']]
# create a buffer distant 150km from the africa boundaries
limits = africa.buffer(1.5)
# get the islands inside the limits
shore_islands = islands.clip(limits)
# display the results
ax = continents.loc[['Africa']].plot()
limits.plot(ax=ax, facecolor='none', edgecolor='grey')
shore_islands.plot(ax=ax, edgecolor='red', linewidth=3)
ax.set_ylabel('Latitude (degrees)')
ax.set_xlabel('Longitude (degrees)')
ax.figure.savefig('output/shore_islands.png', dpi=300)

To identify the islands that are within a given distance from Africa, we first need a polygon that represents Africa. Since we were only given the countries dataset, we have to produce the continent's boundaries by using the ...