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Transforming Data

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SSeekerzero
Last edited Jan 30, 2023
Created on Jan 30, 2023
Forked from Transforming Data

This visualization demonstrates how to use D3.js data transformation techniques to summarize the classic Iris flower dataset. It computes the average sepal length for each iris species using `d3.flatRollup` and `d3.sum`, then displays the resulting summary as formatted JSON text in a `<pre>` element. The code loads data from a local CSV file with `d3.csvParse` and showcases commented-out examples of other transformations like `d3.bin`, `d3.extent`, and `d3.group`.

AI-generated description

Examples of various data transformation techniques, specifically binned aggregation.

MIT Licensed

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Transforming Data

This example analyzes the classic Iris dataset, transforming rows of flower measurements into a concise summary. It displays the average sepal length for each of the three iris species (setosa, versicolor, and virginica) as a formatted JSON text block. The visualization fetches the data from a CSV file, parses it with `d3.csvParse`, and groups the records by species, computing the average value using `flatRollup` and `sum`. The resulting summary is then rendered inside a `<pre>` element, showcasing a simple data aggregation pipeline built with the D3.js framework.

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