Jessamyn Hodge (ProjectCheshire)

ProjectCheshire

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Location:Boston, MA

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graphql-python

Jessamyn Hodge's repositories

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ISO-3166-Countries-with-Regional-Codes

ISO 3166-1 country lists merged with their UN Geoscheme regional codes in ready-to-use JSON, XML, CSV data sets

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cities1000

lat/lon, names of cities with over 1000 people

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json-to-csv

Nested JSON to CSV Converter

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all-the-cities

All the 138,398 cities of the world with a population of at least 1000 inhabitants, in a big JSON array.

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neovis.js

Neo4j + vis.js = neovis.js. Graph visualizations in the browser with data from Neo4j.

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terraformer-geostore

GeoStore module for Terraformer

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iso-3166-2.js

Lookup information about ISO-3166-2 subdivisions

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s2-geometry-library

Automatically exported from code.google.com/p/s2-geometry-library

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iso-3166-2.json

JSON file of ISO 3166-2 subdivisions.

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awesome-neo4j

A curated list of Neo4j resources.

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awesome-world

A collection of awesome world (countries, cities, codes, flags, languages, latitude/longitude, etc.) datasets

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Airports

A JSON database of 28k+ airports with ICAO/IATA codes, names, cities, two-letter country identifiers, elevation, latitude & longitude, and a timezone identifier

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s2map

quick and dirty latlng visualizer

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geojson-cover

generates an s2 cover from geojson

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courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

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efele-tz-world-geojson

GeoJSON version of the world timezone shapefile provided at http://efele.net/maps/tz/world/.

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RacialDotMap

Python code for creating a dataset for a dot density map for every person in the U.S., color-coded by race and ethnicity.

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iso-3166-2

A publicly available dataset containing the countries and administrative divisions as defined in ISO 3166-2.After much research into how to best structure the geospacial data for happiest I made the decision to use ISO 3166-2 as the foundation. This repo contains JSON data representing ISO 3166-2 with the countries and divisions reverse geocoded; designed primarily for import into MongoDB it will be useful to anyone with a need for geospacial data.

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