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Fork of sekhar question1

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Ssriharshakondakindi@gmail.com
Last edited Apr 13, 2024
Created on Apr 13, 2024
Forked from sekhar question1

This example presents a D3.js pie chart that visualizes the distribution of `above 8.5` values across different genres from a CSV file hosted on GitHub. The chart is rendered as an SVG graphic with a legend positioned to the right, using a categorical color scheme. The code asynchronously loads the data via `d3.csv`, processes it, and then computes the pie slices using `d3.pie()` and `d3.arc()`. The visualization includes a legend with colored squares and text labels, applying a semi-transparent fill and black stroke to each slice.

AI-generated description

An example showing the capabilities of VizHub:

  • Loads D3 via UNPKG.
  • Demonstrates use of import from "d3".
  • Demonstrates use of import from local ES6 modules.
MIT Licensed

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Fork of sekhar question1

A pie chart visualizes the distribution of movie genres by the number of films rated above 8.5, loading data asynchronously from a remote CSV file via `d3.csv`. The chart uses `d3.pie` to compute arc angles and `d3.arc` to generate SVG paths, with colors assigned by a `d3.scaleOrdinal` using `d3.schemeCategory10`. A legend on the right displays each genre with a colored square and label. The SVG is rendered with a fixed width of 800 and height of 450, and the visualization highlights proportional genre shares with semi-transparent, black-stroked slices.

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This example displays a pie chart that breaks down genres by the proportion of entries scoring above 8.5. The visualization uses `d3.pie()` to compute arc positions and `d3.arc()` to generate the SVG path data for each slice. A categorical color scheme from `d3.schemeCategory10` fills the segments, with an accompanying legend mapping colors to genre names. Data loads asynchronously from a CSV file via `d3.csv()`.

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