Fork of Loading and Parsing CSV Data

Fork of Loading and Parsing CSV Data

This example demonstrates how to load and parse CSV data using D3.js, displaying summary statistics about the dataset directly on the page. It fetches a CSV file containing CSS named colors from a GitHub gist and calculates the file size in kilobytes, row count, and column count. The visualization uses `d3.csv` to asynchronously retrieve and parse the data, then `d3.csvFormat` to measure its length, and finally updates a `<pre>` element with the results. No charts or graphics are rendered—only the textual metadata is shown.

MMd. Jakir Hosen

Fork of Loading and Parsing CSV Data

This example demonstrates how to load and parse CSV data using D3 v6. It fetches a remote CSV file containing CSS named colors from a GitHub gist and displays basic statistics about the dataset, including its approximate file size in kilobytes and the number of rows and columns. The code uses `d3.csv()` to asynchronously retrieve and parse the data, then `d3.csvFormat()` to measure the raw string length, and writes the results into a `<pre>` element. The visualization is intentionally minimal, focusing on data loading and parsing rather than graphical representation.

BbeauMarko

Fork of Loading and Parsing CSV Data

This visualization demonstrates how to load and parse CSV data using D3 v7, displaying basic statistics about the dataset in a large text format. The example fetches a CSV file containing CSS named colors from a GitHub Gist, then uses `d3.csv` to parse it asynchronously and `d3.csvFormat` to measure the raw data size. It outputs the file size in kilobytes, the total row count, and the number of columns into a `<pre>` element. The code also includes commented alternatives using `fetch` with `async`/`await` and `d3.csvParse` for manual text parsing.

JJacob Pingel Lauridsen

Fork of Loading and Parsing CSV Data

This example demonstrates loading and parsing CSV data using the D3.js library. It fetches a dataset of CSS named colors from a GitHub Gist and displays summary statistics—file size in kilobytes, row count, and column count—in a large preformatted text element. The code uses the `d3.csv` function to fetch and parse the data, then calculates metrics with `d3.csvFormat` and property accessors. A commented alternative shows the same process using the Fetch API with async/await and `d3.csvParse`.

Ccremcircle@gmail.com

Fork of Loading and Parsing CSV Data

This example demonstrates how to load and parse CSV data using D3 v5. It fetches a dataset of CSS Named Colors from a GitHub gist and displays key statistics: the file size in kilobytes, the number of rows, and the number of columns. The code primarily uses `d3.csv()` with a Promise-based `.then()` callback, though commented-out alternatives show fetching text with `fetch()` and `async/await`, plus `d3.csvParse()` for manual parsing. The output renders as plain text inside a `<pre>` element.

Hhung2606

Fork of Loading and Parsing CSV Data

This example displays basic statistics about a CSV file containing CSS Named Colors, showing the file size in kilobytes, row count, and column count. The visualization uses d3.csv to load and parse the remote data from GitHub Gist, then formats the results into a large text message. It also includes commented-out alternatives using fetch with async/await and d3.csvParse, demonstrating different approaches to handling CSV data with D3 version 5.

AAnu Wat

Fork of Loading and Parsing CSV Data

This example demonstrates the basic mechanics of loading and parsing CSV data in D3. It fetches a dataset of CSS named colors from a GitHub gist and displays three summary statistics: file size in kilobytes, row count, and column count. The primary implementation uses D3 v5’s `d3.csv` method, which returns a promise, while commented alternatives show equivalent code using the Fetch API with `async`/`await` and `d3.csvParse`. The output is rendered as plain text inside a large `<pre>` element.

CCheng Tang

Fork of Loading and Parsing CSV Data

CCheng Tang