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Data prep notebooks

This repository contains some Jupyter Notebooks with example code relating to API Highways.

Data prep and import

sdg_datasets.ipynb deals with the parsing and import of data from api.resourcewatch.org. ResourceWatch is provided by the World Resources Institute, and contains many datasets related to several topics related to the Sustainable Development Goals: society, cities, climate, energy, food, forests, and water and oceans

ee_parsing_and_import.ipynb deals with the dataprep and import of datasets provided in Google Earth Engine. Google Earth Engine provides many datasets, both in raster and vector format. GEE is a managed computing enviroment that provides researchers around the world access to massive datasets, from satellite imagery to demographic data.

Data access through the API

Google Earth Engine dataset import and querying.ipynb contains python tooling and examples for a complete 'data pipeline' for a Google Earth Engine dataset, from registering it to making queries to the API.

nightlights_analysis.ipynb deals with using the API for filtering data and consuming it with the Google Earth Engine python API.

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Jupyter notebooks for data prep and exploring

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