All Kiva Challenge Loan Location Coordinates

Context

This is a supplementary dataset to the Data Science for Good: Kiva Crowdfunding challenge. In the Kiva challenge, the kiva_loans.csv file contains a large record of loans with the borrower's locations. This dataset provides the latitude and longitude of these locations.

The original dataset also includes another file loan_themes_by_region.csv, which provides some additional information on geographical locations of the loan themes offered. However, there are significantly more borrower locations than loan theme locations, and these two locations are not always the same. This dataset tries to solve this problem by directly obtaining the geocode of all borrower locations via Google Maps Geocoding API.

Content

There are four columns in the CSV. "Region" and "country" match the corresponding fields in kiva_loans.csv. "Latitude" and "longitude" are self-explanatory. Queries without valid results from the Google Maps API are indicated by latitude=-999, longitude=-999.

The geocodes are not manually validated and should be used with caution. Bad query results may happen due to mistakes in the original dataset or Google Maps' autocorrection.

Acknowledgements

The building of this dataset uses the following API: https://developers.google.com/maps/documentation/geocoding/intro

Inspiration

This dataset can help participants in the Kiva challenge by allowing them to compare location proximity and visualise data on a world/regional map when analysing Kiva's loans. The original purpose of the dataset is for me to visualise loan type clustering results on a world map and find similarities in borrower needs between remote, disjoint regions, however I hope the community will find better, more creative uses for this tiny dataset.