geoMap python package

The geoMap class allows users to visualize the seismic risk profiles of countries and territories around the world. Whether for academic research, business analytics, or educational purposes, geoMap provides a platform to enhance the understanding of complex spatial relationships and promote informed decision-making processes.

Functions:

__init__ Method:

Use this method to create a geoMap object for mapping.

Parameters:

• code: Country code for the map (default is 'ALL').
• var: Index of the selected variable (default is 3).
• colorscale: Index of the selected colorscale (default is 0).
• countryCenter: Boolean to specify whether to center the map on the selected country.
• showFaults: Boolean to specify whether to show fault lines on the map.

printOptions Method:

Use this method to see what options are available for customizing your geoMap object.

Parameters:

• data: String indicating the type of options to print ('codes', 'variables' or 'colorscales').

Prints:

• List of country codes, variable options, or color scales.

map Method:

Once you have created your geoMap object, call this method to draw a map.

Parameters:

• None

Returns:

• Choropleth map using Plotly Express.

Example Maps

Hovering over a fault will display the fault's danger level. Hovering over a country will display the country's name, code, and value for the variable of interest.

1: World Map (Default)

code = 'ALL' (world map)

var = 3 (countries colored according to variable 3: GDP per capita)

countryCenter = True (map is centered on the specified country - in this case, all)

colorscale = 0 (viridis)

gm1 = geoMap()
gm1.map()

2: Japan

code = 'JPN' (Japan)

var = 4 (countries colored according to variable 4: total number of buildings)

countryCenter = True (map is centered on the specified country)

colorscale = 1 (Blues)

gm2 = geoMap(code = 'JPN', var = 4, countryCenter = True, colorscale = 1)
gm2.map()

3: Colombia

code = 'COL' (Colombia)

var = 1 (countries colored according to variable 1: Population Density (Log Scale))

countryCenter = False (map is not centered on the specified country)

colorscale = 2 (Purples)

gm3 = geoMap(code = 'COL', var = 1, countryCenter = False, colorscale = 2)
gm3.map()

4: Haiti

code = 'HTI' (Haiti)

var = 3 (countries colored according to variable 3: GDP per Capita)

countryCenter = True (map is centered on the specified country)

colorscale = 0 (viridis)

gm4 = geoMap(code = 'HTI', var = 3, colorscale = 0)
gm4.map()

5: Indonesia

code = 'ALL' (world map)

var = 5 (countries colored according to variable 5: Government Effectiveness)

countryCenter = True (map is centered on the specified country)

colorscale = 1 (Blues)

gm5 = geoMap(code = 'IDN', var = 5, showFaults = True, colorscale = 1)
gm5.map()

Data Sources

• Fault Lines from the Global Block Model

Country Variables

• Population (World Bank, 2021)
• Population Density (World Bank, 2021)
• GDP (World Bank, 2021)
• GDP per Capita (World Bank, 2021)
• Government Effectiveness (World Bank, 2021)
• Buildings Total (Yepes-Estrada et al., 2023)