Fork of Fork of Loading and Parsing CSV Data

Fork of Loading and Parsing CSV Data

This example displays a large-format text summary of a CSV dataset, specifically the CSS Named Colors collection, showing its size in kilobytes, row count, and column count. The visualization uses D3.js version 5 to load and parse the remote CSV file via `d3.csv`, then formats the statistics using `d3.csvFormat`. The resulting message is rendered inside an HTML `<pre>` element, with the code demonstrating both the primary `d3.csv` approach and alternative commented methods using `fetch`, async/await, and `d3.csvParse`.

Vvram80

Fork of Loading and Parsing CSV Data

This example displays a plain-text summary of the CSS Named Colors CSV dataset loaded from a remote gist, showing its size in kilobytes, row count, and column count. It uses D3 v5’s `d3.csv` method to fetch and parse the data, then computes the formatted text with `d3.csvFormat`. The code also demonstrates alternative approaches commented out, including `fetch` with `async`/`await` and `d3.csvParse`, as well as a "pyramid of doom" pattern. The rendered output appears in a large `<pre>` element.

Llingfa

Fork of Loading and Parsing CSV Data

This example demonstrates how to load and parse a CSV file containing CSS Named Colors, then displays the file size, row count, and column count as a text summary. The code uses D3 v5’s `d3.csv` method to fetch and parse the remote CSV data, while also providing commented alternatives using the Fetch API with `async`/`await` and `d3.csvParse`. The rendered output is a simple `<pre>` element with large text, showing the parsed dataset’s basic metrics.

Cchar0496

Fork of Loading and Parsing CSV Data

This example loads a CSV file containing CSS named colors and displays a text summary of its size and shape. The visualization simply reports the file size in kilobytes, the number of rows, and the number of columns, rendered in a large `<pre>` element. It uses the D3 v5 library's `d3.csv` method to fetch and parse the remote CSV data, and `d3.csvFormat` to compute the data size. The code also includes commented-out alternatives using `fetch` with async/await and a nested Promise structure.

BBruno Albuquerque

Fork of Loading and Parsing CSV Data

This example demonstrates loading and parsing CSS Named Colors CSV data, displaying the file size, row count, and column count as text. It uses `d3.csv` to fetch and parse the remote CSV file from a GitHub Gist, then formats the results with `d3.csvFormat` to calculate kilobytes. A commented alternative shows the same process using `fetch`, `async`/`await`, and `d3.csvParse`. The visualization is minimal—a single `<pre>` element updated with the parsed data summary, built with D3 v5 in a React framework.

Llaurence beattie

Fork of Loading and Parsing CSV Data

This example displays a summary of a CSV dataset containing CSS named colors. It computes the file size in kilobytes, the number of data rows, and the number of columns, then renders these three statistics in a large HTML `<pre>` element. The code uses the D3.js v5 library’s `d3.csv` function to fetch and parse the remote CSV file, and `d3.csvFormat` to calculate the size of the formatted data. The visualization is minimal, focusing on textual output rather than graphical representation.

SS-Zins

Fork of Loading and Parsing CSV Data

This example demonstrates loading and parsing CSV data by displaying a summary of the CSS Named Colors dataset in an HTML <pre> element. The code uses d3.csv from D3 v5 to fetch the remote CSV file, then calculates and displays the file size in kilobytes, row count, and column count. A commented-out alternative shows the same result using the Fetch API with async/await and d3.csvParse, illustrating two different approaches to handling asynchronous data loading in a React context.

Ggeethakanniah

Fork of Loading and Parsing CSV Data

This example shows a summary of the CSS named colors dataset, displaying the file size in kilobytes, row count, and column count in a large <pre> element. It loads the CSV from a GitHub gist using `d3.csv` and parses it into an array of objects. The code then formats the data back to CSV with `d3.csvFormat` to calculate its size, and reads the row and column counts directly from the parsed array and its `columns` property. The result is rendered as plain text into the DOM.

SShmuel Leider