Mexcio Regions Pass 2

Mexico Waste 2018 Choropleth Pass3

This choropleth maps municipal solid waste generation across Mexican states for 2018, with each state filled according to its total waste in kilograms using a viridis sequential color scale. Missing data appears in blue, while graticules and state interiors are drawn as SVG paths. The visualization uses d3.geoMercator and d3.geoPath for geographic projection, with TopoJSON data from arcgis.com converted via mapshaper. React manages state and lifecycle, loading CSV waste data and zone metadata through d3.csv.

87% match

Mexico map

A choropleth-style map of Mexico's regions rendered as SVG paths using a Mercator projection, with each state outlined in yellow against a blue graticule grid. The visualization loads geographic data from a TopoJSON file hosted as a GitHub gist, processed with the `topojson.feature` API, while D3's `geoPath` and `geoMercator` handle the projection and path generation. The React component fetches the data asynchronously and displays a loading message until the map is ready, with styled fill and stroke colors applied via CSS classes.

VVAbhiram99

86% match

Mexico Waste 2018 Choropleth Pass4

This choropleth displays municipal solid waste generation across Mexican states for 2018, using a viridis sequential color scale to encode kilograms of waste with a blue fill for missing data. The visualization renders geographic boundaries via d3.geoPath with a geoMercator projection, driven by TopoJSON state geometries from ArcGIS data. React manages the component lifecycle, while d3.csv loads the waste dataset and d3.scaleSequential handles color mapping, with an accompanying linear gradient legend documenting the scale in kilograms.

86% match

Mexico Region Map ( D3 & React & TopoJSON )

This example displays a map of Mexico rendered as a single-color choropleth, with state boundaries outlined and a graticule overlay. The visualization uses a Mercator projection via `d3.geoMercator` with the map centered on the country. The geographic data is loaded from a TopoJSON file fetched with `d3.json` and converted to GeoJSON using `topojson.feature`, with the shapes drawn by `d3.geoPath`. The implementation is built with React, managing the asynchronous data fetching through a custom hook and rendering the SVG marks as React components.

86% match

Mexico map

This example displays a choropleth map of Mexico’s regions, rendered as SVG paths. Using D3’s `geoMercator` projection and `geoPath`, it draws country boundaries and graticules, with each region filled in red and outlined in yellow. The map is built with React, fetching TopoJSON data from a gist, converted via `topojson.feature`. The visualization omits data for missing regions, which are not plotted.

RRevanthReddyG

Fork of Mexico Waste 2018 Choropleth Pass2

This choropleth maps municipal solid waste generation across Mexican states using a Mercator projection, with a sequential viridis color scale encoding waste kilograms from a 2018 dataset. The visualization renders geographic boundaries and graticules via `d3.geoPath` and `d3.geoGraticule`, while React manages state and data loading through custom hooks. State geometries come from TopoJSON processed with `topojson.feature` and `topojson.mesh`, and the color encoding uses `d3.scaleSequential` with `d3.interpolateViridis`. Missing regions appear blue, and CSV data is fetched and parsed with `d3.csv`.

Mexico map

This choropleth-style map displays the regions of Mexico, with each state rendered as a closed path. The visualization uses a Mercator projection, centered on the country’s coordinates, and draws a graticule overlay in a contrasting color. The map is built with D3 v6's `geoMercator` and `geoPath` functions within a React component. State boundaries originate from ArcGIS data, which is converted to GeoJSON via mapshaper and then loaded through D3's `json` method in the `getMexico.js` file.

PPavaniMangugari

Fork of Mexico Waste 2018 Choropleth Pass4

This choropleth maps waste generation in kilograms across Mexican states for 2018, using a viridis sequential color scale to encode values from the waste dataset. It renders geographic boundaries with the `geoMercator` projection and `d3.geoPath`, applying distinct styling to state interiors and graticules for visual clarity. The visualization is built with React, loading TopoJSON state geometries and CSV waste data, while a custom legend with linear gradient ticks displays the mapping from color to waste quantities. Missing data regions appear in blue, and a tooltip context is prepared for potential interactivity.

00rtiz