As part of my geospatial master's program at UCLA, I have been learning to use Python and R for performing analysis on various datasets. The following are some of the notebooks I've created on Kaggle or Google Colab which demonstrate what I have learned along the way. I really enjoy writing notebooks and am impressed with how much you can do with a very small amount of code using libraries such as Pandas, GeoPandas, and MatPlotLib.

World Bank Economics Analytics

This notebook explorers some economic indicators downloaded from the World Bank data store. This example uses mapclassify to generate class breaks on the data using the Fisher Jenks scheme and then beautifies the class breaks for display in the legend.

Notebook »

Income Inequality Data Analytics

This notebook visualizes income inequality data geospatially, comparing various years altogether. I used Python GeoPandas to read, merge, and aggregate Gapminder income inequality data by country and year.

Notebook »

Point Density Measures

In this notebook, I created hexagonal geometries based on point density from the Denver Crime vector dataset. I then used the geometries to calculate a density measure for a list of Denver AirBnB locations. Even though this was a fictional data study, exploring the concept of point density measure analysis was exciting!

Notebook » Blog »

Denver AirBnB Analytics

This notebook demonstrates using GeoPandas, Pyplot, and other libraries to analyze Airbnb data in the Denver area. The interesting sections of code include address geocoding using Nominatim, generating a buffer around a location, performing spatial joins, and calculating distance to local points of interest.

Notebook » Blog »

Contour Volumetric Values

This notebook explores using various Python contour engine libraries for generating contour maps based on elevation and energy product volumes.

Notebook » Blog »

Gender Inequality Analytics

This notebook explores the Gender Inequality Index (GII) data downloaded from Human Development Reports.

Notebook »

Power Plant Capacity

This notebook will use GeoPandas, pyplot, and matplotlib to create a geoplot of power plant capacity in Australia. One interesting piece of code was using GeoPandas sjoin and bulk_query methods to perform a spatial intersections.

Notebook » Blog »

Global Financial Crisis Analytics

This notebook explores the behavioral financial stability dataset from Harvard Business School. This example performs data aggregations using Pandas as well as visualizing the results using GeoPandas geoplots and charts.

Notebook »

Gapminder Data Mapping

This was one of my first notebooks. It is a simple geoplot of Gapminder data. One plot uses choropleth style mapping and the other uses scaled point mapping.

Notebook »

Python map using Folium

This example displays COVID-19 deaths for the first quarter of 2021. I used GeoPandas to aggregate the data and create a Folium map to visualize the results.

Notebook » Blog »