Skip to main content
SimilarExport ZIP
100%

Aggregation by Country using Map

✓ Published1🌍 Public
Ssophburke
Last edited Oct 23, 2019
Created on Oct 23, 2019

This example visualizes the geographic distribution of video views for Harvardx and MITx online courses in 2013. Circles positioned using a Mercator projection show total views per location, with a tooltip revealing the country name and view count. The visualization combines React for component rendering with D3’s `geoMercator`, `geoPath`, and `scaleSqrt` for sizing. It overlays aggregated view data from a CSV dataset onto land and graticule shapes generated from TopoJSON world atlas data.

AI-generated description

This is a visualization of the Harvardx/MITx Course-Person Dataset for the academic year 2013. The data shows the number of video views of the online courses, represented by the circles on the map. The data can be found here.
</br> The world map behind the points is a Mercator type map using the World Atlas TopoJSON. The points are off by a small fraction (down and to the left) however it fits much better on the Mercator projection over the Natural Earth projection. When the user hovers over each point, they can see the latitude and logitude of that deployment.

MIT Licensed

Similar vizzes

Loading thumbnail…

Aggregation by Country using Map

This example visualizes the total video views from the Harvardx/MITx Course-Person Dataset, aggregated by country and displayed as graduated circles over a Mercator-projected world map. The map uses d3.geoMercator and d3.geoPath to render landmasses, graticules, and country borders from World Atlas TopoJSON, while d3.scaleSqrt maps view counts to circle radii. Points are positioned using d3.projection, and hovering reveals the country and view count via an SVG `<title>` tooltip.

Mmkt-ds
94% match
Loading thumbnail…

Aggregation by Country using Map

This visualization maps video views from the Harvardx/MITx course-person dataset for 2013, with circle size encoding view counts per location. It uses a Mercator projection via `geoMercator` and `geoPath` from d3, rendering country boundaries from World Atlas TopoJSON and graticules. React components manage state with `useDataViews` and `useDataMap`, while circles display tooltips showing country names on hover.

CCurran Kelleher
94% match
Loading thumbnail…

Aggregation by Country + Dropdown

This visualization displays the number of video views for HarvardX/MITx online courses in 2013, with circles sized by view count on a world map. A dropdown menu filters the displayed data by course. The map uses a Mercator projection via `geoMercator` and `geoPath`, with geographic features from the World Atlas TopoJSON. View data comes from a CSV file loaded with `d3.csv`. The visualization is built with React components and D3 scales (`scaleSqrt`) for circle sizing.

Ssophburke
93% match
Loading thumbnail…

From Chen Ding: Aggregation by Country using Excel + Dropdowns!

This example visualizes the number of video views for HarvardX/MITx online courses in the 2013 academic year. Circles, sized by total views, are positioned on a world map according to viewer location, with a dropdown menu to filter by specific course. A tooltip reveals the country and view count for each circle. The visualization uses a Mercator projection via `geoMercator`, renders map features with `geoPath`, and calculates the circle sizing using `scaleSqrt` from D3 v5. The map data comes from the World Atlas TopoJSON, while view data is loaded from a CSV file.

Ssophburke
89% match
Loading thumbnail…

From Chen Ding: Aggregation by Country using Excel + Dropdowns!

This example visualizes the number of video views for Harvardx/MITx online courses in 2013, with circles sized proportionally to view counts and positioned by geographic coordinates on a world map. A dropdown menu filters the view by specific course, and hovering over a circle reveals the country and total views. The map uses a Mercator projection via D3’s `geoMercator` and `geoPath` for landmasses and graticules, while `scaleSqrt` determines circle sizes. Data is loaded as CSV and TopoJSON, with the view rendered as React-driven SVG elements.

JJoker-tr
89% match
Loading thumbnail…

Aggregation by Country + Dropdown

This example visualizes video views from the Harvard/MITx online course dataset (academic year 2013) on a world map. A dropdown menu filters which course’s view counts are displayed as circles, with radius encoding the total views per country via `scaleSqrt`. Hovering reveals the country name and view count. The map uses a Mercator projection (`geoMercator`) with `geoPath` to render land and graticules from World Atlas TopoJSON, while the interface is built with React and the `react-dropdown` component.

Ssophburke
89% match
Loading thumbnail…

Sophie's version: Aggregation by Country using Excel

This example visualizes the total video views for HarvardX and MITx online courses in 2013, aggregated by country and shown as circles on a world map. Circle size encodes view count, and hovering reveals the country and number of views. The map uses a Mercator projection built with D3’s `geoMercator`, `geoPath`, and `geoGraticule`, layered with land and interior boundaries from the World Atlas TopoJSON. Data is loaded from a remote CSV via D3’s `csv` function, and the circles are positioned using the projection, with their radius scaled by `scaleSqrt` in SVG.

Ssophburke
88% match
Loading thumbnail…

Harvard X-MITx Viewership by Country

This example maps HarvardX-MITx course viewership by country for AY2013. A geoMercator projection with d3.geoPath renders the world map from World Atlas TopoJSON, while overlaid circles mark viewer locations using linear scales derived from the dataset. The visualization uses React to manage state and render SVG elements, with d3.json and d3.tsv loading the map topology and viewership data. Graticules, landmasses, and interiors are styled separately to distinguish geographic features from data points.

Ssophburke
88% match