isidro12345

@isidro12345·4 public vizzes

Choropleth Map Project

This choropleth map visualizes global economic classifications by coloring each country according to a categorical scale derived from the `economy` property in the World Atlas dataset. The map uses a natural Earth projection and renders as SVG with D3’s `geoPath` and `geoNaturalEarth1`. Country boundaries are drawn with thin strokes, and hovering over a country turns it gray while a tooltip displays the country name and its economy group. A custom color legend, built with `scaleOrdinal` and `schemeSpectral`, appears in the lower-left corner. The map supports zooming through D3’s zoom event handler.

Sep 22, 2019

Loading thumbnail…

Choropleth Map Project

This choropleth map colors world countries by their economy category using an ordinal color scale with a spectral scheme. It renders geographic boundaries via the `geoPath` projection and `geoNaturalEarth1`, with data loaded from the world-atlas TopoJSON and TSV files. Hovering highlights a country in gray. The legend, built with custom code, uses circles and text to display the economy categories, while the map supports zooming through an event-driven `zoom` interaction.

Sep 22, 2019

Loading thumbnail…

Scatterplot project

This scatterplot charts country economies as circles, with the x-axis representing economy values from a CSV file and the y-axis listing country names. The visualization uses D3 v5 APIs including `scaleLinear`, `scalePoint`, `axisLeft`, and `axisBottom` to render axes, while `select`, `append`, and `data` methods position circles at scaled coordinates. The SVG canvas is 960 by 500 pixels, and the chart includes a title noting countries that consume the most electricity. The graph remaps numeric string values from the data source using `+d.economies` before rendering.

Sep 22, 2019

Loading thumbnail…

Bar Chart Project

This bar chart displays the top ten economies by country, with bars scaled to represent economic values in thousands. Built with D3 v5, the visualization uses `d3.csv` to load data from a CSV file, `scaleLinear` for the x-axis, and `scaleBand` for categorical y-axis positioning. The SVG rendering includes axes via `axisLeft` and `axisBottom`, while rectangular elements are appended and sized programmatically. The chart, based on Curran Kelleher’s tutorial, is entirely client-side with no interaction.

Sep 22, 2019