Fork of Rendering Marks and Channels with React & D3

Rendering Marks and Channels with React & D3

This example visualizes the top 20 countries by COVID-19 cases using a horizontal bar chart rendered as SVG. React manages the component state and lifecycle, fetching data from a CSV file via d3.csv, while d3.scaleBand and d3.scaleLinear create the categorical and quantitative scales. The chart displays green bars alongside custom gridlines and tick labels generated through React’s map function, with the data sourced from a GitHub gist containing pandemic statistics.

SSumanya4

93% match

Fork of ICE-6: Rendering Marks and Channels with React & D3

This visualization displays the top 20 countries by COVID-19 cases on January 28, 2020, using a horizontal bar chart rendered as SVG. React manages the component state and DOM elements, while D3 v5 provides scales (`scaleBand`, `scaleLinear`), CSV data loading, and tick generation. The data comes from a GitHub-hosted CSV file, and bars and axes are drawn as React elements positioned by D3 scales. Styling is handled via CSS, with green bars and red gridlines.

SSumanya4

Fork of ICE-6: Rendering Marks and Channels with React & D3

This example shows a horizontal bar chart of COVID-19 case counts for 20 countries, using length as a visual channel to encode the number of reported cases on a given date. The chart is built with React components that render SVG elements, while D3’s `d3.csv`, `scaleBand`, and `scaleLinear` handle data loading and scaling. Axes are manually constructed by mapping tick values to SVG lines and text labels. The data comes from a remote CSV file containing daily case numbers per country.

Fork of ICE-6: Rendering Marks and Channels with React & D3

This bar chart visualizes COVID-19 cases across the top 20 countries, using horizontal bars to compare case counts. The visualization is built with React and D3 v5, where React manages state and renders SVG elements while D3 scales handle data mapping. The code uses `d3.scaleBand` for the categorical y-axis, `d3.scaleLinear` for the quantitative x-axis, and `d3.csv` to load the dataset from a GitHub gist. Tick marks and axis labels are generated manually through React's array mapping rather than using D3's axis components.

Fork of ICE-6: Rendering Marks and Channels with React & D3

Fork of ICE-6: Rendering Marks and Channels with React & D3

This bar chart displays COVID-19 case counts for the top 20 countries, ranked by their reported infections on January 28, 2020. Using React with D3 v5, the visualization renders SVG rectangles scaled by population data from a CSV file, with D3’s `scaleBand` and `scaleLinear` mapping country names and case values. Axis ticks and labels are generated manually via `.map()` and React elements, while the data is loaded asynchronously with `d3.csv`. The chart shows a horizontal bar layout with green rectangles and red gridlines, highlighting comparative case volumes across countries at that early pandemic date.

90% match

Fork of Fork of ICE-6: Rendering Marks and Channels with React & D3

This bar chart displays the top 20 countries by reported COVID-19 cases, using horizontal bars to compare values. The visualization loads CSV data via `d3.csv` and slices the first 20 rows, with React managing state and rendering SVG elements. Scales are created using `d3.scaleBand` for the y-axis and `d3.scaleLinear` for the x-axis, with axis ticks manually generated and mapped to React components. Each bar is drawn as a `rect` element, with the x-axis grid lines and tick labels rendered as SVG `line` and `text` elements.

Bblikitha

90% match