FHIV/AIDS Choropleth Map

HIV/AIDS Choropleth Map

This choropleth map visualizes the global share of the population infected with HIV/AIDS in 2017, using a yellow-to-red sequential color scale to indicate prevalence rates. It renders a Natural Earth projection with graticules and country borders, and colors each country based on data from the IHME dataset, with gray indicating missing values. The visualization is built with React and D3 v5, using `d3.geoPath` for map geometry, `d3.scaleSequential` with `interpolateYlOrRd` for color encoding, and TopoJSON to load world atlas boundaries.

SSai Phaltankar

FHIV/Aids Choropleth Map

A choropleth map visualizes the global prevalence of HIV/AIDS among adults aged 15–49 in 2017, with countries colored on a yellow-to-red sequential scale by infection percentage and black for missing data. The map uses a natural Earth projection via `d3.geoNaturalEarth1` and renders country boundaries from World Atlas TopoJSON using `d3.geoPath`. Data comes from a CSV of IHME estimates filtered by year. The visualization is built with React, SVG, and D3 v5, applying a `scaleSequential` with `interpolateYlOrRd` for color encoding.

Nnexus1058

HIV/AIDS Choropleth Map

This choropleth map visualizes the global share of the population infected with HIV/AIDS for the year 2017, using a yellow-orange-red color scale to represent prevalence rates. Countries with missing data appear in gray. The visualization is built with React and D3 v7, using `geoNaturalEarth1` and `geoPath` to render world countries from TopoJSON data, with geographic graticules and interiors drawn as overlays. The data comes from a CSV file containing HIV prevalence statistics from IHME.

BBen Seebeck

HIV/AIDS Choropleth Map

This choropleth map visualizes the global share of the population infected with HIV/AIDS among adults aged 15–49 for the year 2017, using a yellow-to-red sequential color scale. It renders country boundaries as SVG paths via d3.geoPath and d3.geoNaturalEarth1, with graticule and interior borders drawn from TopoJSON data. Missing country data appears white. The map is built with React hooks for data loading and D3’s scaleSequential with interpolateYlOrRd, pulling HIV prevalence from an IHME CSV dataset.

KKazushige Okuma

Fork of HIV/AIDS Choropleth Map

This choropleth map visualizes the share of the population infected with HIV/AIDS for the year 2017, using a yellow-orange-red sequential color scale to encode prevalence rates. Countries without data appear in gray. The map is rendered with SVG paths generated by d3.geoPath and the geoNaturalEarth1 projection, with graticules and country boundaries drawn from World Atlas TopoJSON data. The visualization is built in React, fetching CSV data via d3.csv and mapping ISO country codes to numeric identifiers for joining with the geographic features.

Eevers-codeshop-ai

HIV/AIDS choropleth map

This choropleth map visualizes the global share of the population infected with HIV/AIDS for the year 2017, using a yellow-to-red sequential color scale to encode prevalence. The visualization renders country polygons via `d3.geoPath` with a Natural Earth projection, overlaying graticule lines and interior borders. Data from the IHME dataset is joined to map features through ISO alpha-3 to numeric country codes, with missing countries shown in gray. The React component uses `d3.scaleSequential` and `d3.interpolateYlOrRd` for color encoding, with TopoJSON from world-atlas providing the geographic boundaries.

AAndrea Picciau

HIV/AIDS Choropleth Map

A choropleth map visualizes the share of the population aged 15-49 infected with HIV/AIDS in 2017, using a yellow-orange-red sequential color scale on a Natural Earth projection. The map renders countries as SVG paths via d3.geoPath, with gray fill for missing data, and includes graticules and interior borders. Data comes from the IHME HIV prevalence CSV and country codes from the ISO-3166 dataset, processed in React with d3-scale and topojson.

LLaura Johnson

HIV/AIDS Choropleth Map

This interactive choropleth map visualizes the global share of the population infected with HIV/AIDS in 2017, using data from OurWorldInData. Countries are colored on a yellow-to-red sequential scale based on prevalence, with gray indicating missing data. The visualization is built with React, rendering SVG shapes through d3.geoPath and a geoNaturalEarth1 projection, while d3-geo graticules and topojson mesh outlines delineate geographic boundaries. Country codes from the ISO-3166 dataset link the CSV data to world-atlas map features.

AAnthony Ynami