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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

97% match

Fork of Fork of Fork of Fork of Sports List

This visualization presents a ranked bar chart of popular sports in 2021, sourced from a CSV dataset and rendered as an SVG via React. The code uses d3.csv for data loading, d3.scaleBand and d3.scaleLinear for positioning, and d3.max for domain calculation. Horizontal bars display each sport’s match count, with axis ticks and labels generated manually using d3.ticks. The chart is built with React hooks (useState, useEffect) and ReactDOM rendering, with D3 selections integrated for scaling and formatting.

Fork of Fork of Fork of Fork of Fork of Sports List

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

Fork of Sports List

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.

Fork of Sports List

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.

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A horizontal bar chart displays the popularity of eleven sports in 2021, with purple bars representing match counts on a blue grid. The visualization loads data from a CSV file using `d3.csv` and renders an SVG via React. It employs `scaleBand` for the categorical y-axis and `scaleLinear` for the quantitative x-axis, with `d3.max` determining the domain, while axis ticks are manually generated from the scales.

Ppavan0828

94% match

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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.

93% match

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This example visualizes the most famous sports of 2021 using a horizontal bar chart. The chart displays the number of matches for each sport, with sports ordered alphabetically along the vertical axis and match counts on the horizontal axis. The code uses D3 v5 utilities like scaleBand, scaleLinear, and max to create the scales, while CSV data is loaded via d3.csv. The visualization is rendered as SVG elements within a React component using the react and react-dom libraries, with purple bars representing each sport's match count.