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 the top 10 most populous countries for 2019, using horizontal bars to encode population size. The visualization is built with React and D3 v5, where React manages the component state and rendering of SVG elements while D3’s `csv`, `scaleBand`, and `scaleLinear` handle data loading and scaling. Axes are manually rendered as SVG groups with tick marks, and the data originates from a GitHub-hosted CSV file.

Ppreethamkesa

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

Ppreethamkesa

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

This bar chart shows the top 10 most populous countries in 2019, with each bar's length proportional to the country's population. The visualization is rendered as an SVG using React and D3 v5, with D3's `scaleBand` and `scaleLinear` functions mapping country names and population values to screen coordinates. The chart includes labeled axes for population counts and country names. Data is loaded asynchronously from a CSV file using D3's `csv` function, and the top 10 rows are displayed after sorting.

Eeravellisaimeghana

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

Eeravellisaimeghana

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

A bar chart displays the top 10 most populous countries, with bars ordered by country name and sized by 2019 population. The visualization is built using React and D3.js (v5), loading data from a CSV file and rendering SVG elements. It uses `scaleBand` for the y-axis, `scaleLinear` for the x-axis, and `csv` to fetch and parse the data, with React managing the component state and rendering.

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

A horizontal bar chart displays the top 10 most populous countries for 2019, with country names on the y-axis and population values on the x-axis. The visualization is built using React for component structure and D3.js for data processing and SVG rendering. It fetches CSV data from a remote source, maps population values, and uses D3's `scaleBand` and `scaleLinear` for axes and bar positioning. D3's `csv` function loads the data, which is then rendered as SVG rectangles within a React SVG element.

Ppreethamkesa

BBajiSharifPatan@my.unt.edu

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

This visualization displays the top 10 most populous countries in 2019 as horizontal bars, with country names on the y-axis and population values on the x-axis. The chart is built using React and D3, leveraging `scaleBand`, `scaleLinear`, and `max` from d3.v5 to compute scales and domains from CSV data. SVG rectangles render the bars, with custom tick labels and gridlines drawn manually through JSX. Data is loaded asynchronously via `csv` from a GitHub gist URL.

BBajiSharifPatan@my.unt.edu

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

This bar chart displays the top 10 most populous countries using data from a CSV file. The visualization renders SVG rectangles with countries on the y-axis and population on the x-axis, using scales from d3-scale and React components for markup. The code loads data with d3.csv, applies a linear scale for population and a band scale for countries, then manually renders grid lines and axis labels inside a React SVG.