data

Sports List

This visualization displays a bar chart of the top eleven sports in 2021 based on match counts, sorted vertically with a purple bar for each sport. The code uses D3 v5 (including `scaleBand`, `scaleLinear`, `csv`, and `max`) within a React component to load data from a GitHub-hosted CSV and render the chart as an SVG. Axes are manually drawn with ticks and gridlines, while text labels for sports appear on the left.

MManasaPatange

91% match

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This example displays the 11 most popular sports of 2021 ranked by number of matches, rendered as a horizontal bar chart using SVG. The chart uses React with hooks to load and manage the CSV data, while D3 v5 provides the scales, axes, and shape rendering. The bars are colored purple and include labeled tick marks for both axes, with the x-axis scaled linearly by match count. The code uses `scaleBand` for the categorical sports names and `scaleLinear` for the numeric values.

89% match

Untitled

This example shows the number of matches for the top 11 sports in 2021 as horizontal bars, using a bar chart layout. The visualization uses React with d3-scale functions (scaleBand, scaleLinear) to map data to positions and sizes, and renders SVG elements directly. Data is loaded from a CSV file via d3.csv. The chart includes axis ticks generated manually, with bars filled in purple and axis lines in blue.

Aakhil kata

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A horizontal bar chart displays the popularity of sports in 2021, ranking eleven sports by match counts from a CSV dataset. The visualization uses React with D3 v5, employing `d3.csv`, `scaleBand`, and `scaleLinear` to map data to SVG rectangles. Purple bars represent match totals, with axes drawn using `xScale.ticks()` and manual tick text. The chart renders client-side, fetching data from a GitHub gist URL.

SSaiSree0122

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This visualization presents a bar chart of the most famous sports in 2021, using horizontal bars ordered by rank to display the number of matches for each sport. It loads data from a CSV file via `d3.csv` and renders the chart with React, using `scaleBand` for the categorical y-axis and `scaleLinear` for the numeric x-axis. The SVG output includes grid lines and axis tick labels generated by D3’s scale methods, with bars filled in purple.

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This visualization displays the popularity of sports in 2021 using horizontal purple bars. The chart ranks the top 11 sports based on match counts, with a blue gridline background and labeled axes. Built with React and D3 v5, it uses `d3.csv` to load data from a GitHub gist, `scaleBand` for the y-axis, and `scaleLinear` for the x-axis, rendering all elements as SVG rectangles.

SSaiSree0122

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A horizontal bar chart displays the popularity of sports in 2021, ranking eleven sports by match count. The visualization uses React with D3.js v5, loading data from a CSV file and rendering the chart as an SVG. D3's `csv` function parses the data, while `scaleBand` and `scaleLinear` position bars and axes. The bars themselves are SVG rectangles filled with purple, and the chart includes axis ticks and labels generated with D3's `scaleLinear` and `scaleBand` methods.

Fork of Fork of Sports List

This visualization displays the top 10 famous sports in 2021, with each sport's popularity measured by the number of matches played. The horizontal bar chart renders as an SVG using React and d3.js, with the data loaded from a CSV file via d3.csv. The chart uses d3.scaleBand for the y-axis sport categories, d3.scaleLinear for the x-axis match counts, and d3.max to compute the scale domain. The code also utilizes React's useEffect and useState hooks for fetching and storing the data.