#!/usr/bin/env python
# coding: utf-8

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import geopandas as gpd
import pandas as pd
import matplotlib.pyplot as plt


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# set path to shapefiles
path = ('C:/Users/jtrum/world_bank/luanda_angola/')


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# read shapefiles
angola0 = gpd.read_file(path + 'gadm41_AGO_0.shp')
angola1 = gpd.read_file(path + 'gadm41_AGO_1.shp')
angola2 = gpd.read_file(path + 'gadm41_AGO_2.shp')
angola3 = gpd.read_file(path + 'gadm41_AGO_3.shp')


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# plot shapefiles as a 2 by 2 grid
fig, ax = plt.subplots(2, 2, figsize=(10, 10))
angola0.plot(ax=ax[0, 0], color='white', edgecolor='black')
angola1.plot(ax=ax[0, 1], color='orange', edgecolor='black')
angola2.plot(ax=ax[1, 0], color='green', edgecolor='black')
angola3.plot(ax=ax[1, 1], color='teal', edgecolor='black')
plt.show()


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angola0


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angola1


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angola2


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angola3


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# extract Luanda, Angola from luanda1
luanda1 = angola1[angola1['NAME_1'] == 'Luanda']
luanda1


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# extract Luanda, Angola from luanda2
luanda2 = angola2[angola2['NAME_1'] == 'Luanda']
luanda2


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# extract Luanda, Angola from luanda3
luanda3 = angola3[angola3['NAME_1'] == 'Luanda']
luanda3


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# plot luanda2
luanda2.plot(color='orange', edgecolor='black')
plt.show()


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# merge luanda2 to be one polygon
luanda2clean = luanda2.dissolve(by='NAME_1')

# plot luanda2clean
luanda2clean.plot(color='orange', edgecolor='black')
plt.show()


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# export data folder path
export = (path + 'exports/')


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# export as geojson
luanda2clean.to_file(export + 'luanda2clean.geojson', driver='GeoJSON')


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