Fork of Loading and Parsing CSV Data

Fork of Loading and Parsing CSV Data

This example demonstrates how to load and parse CSV data from a remote source using D3.js. It displays the file size, row count, and column count of the CSS Named Colors dataset in a large text format. The code uses `d3.csv` to fetch and parse the data asynchronously, then accesses the resulting parsed array and its `.columns` property. An alternative approach using `fetch`, `async`/`await`, and `d3.csvParse` is provided in comments, along with a deprecated callback-based "pyramid of doom" pattern.

CCatalina Vajiac

Fork of Loading and Parsing CSV Data

This interactive example demonstrates the process of loading and parsing CSV data from a remote URL, fetching the CSS Named Colors dataset. Using D3.js v5, it displays the file size in kilobytes, the number of rows, and the number of columns in a large text format. The primary approach employs `d3.csv`, with commented-out alternatives showing `fetch` with `async`/`await` and `d3.csvParse`. The interface is minimal, rendering the computed statistics within a `<pre>` element.

TTyler Brown

Fork of Loading and Parsing CSV Data

This example demonstrates how to load and parse CSV data from a remote URL, displaying the file size in kilobytes, row count, and column count as plain text. It uses the `d3.csv` function from D3 v5 to fetch and parse the CSS Named Colors dataset. The code also includes commented-out alternatives using `fetch`, async/await, and `d3.csvParse`, showing different approaches to handling asynchronous data loading. The visualization itself is minimal, prioritizing the data-loading process over graphical representation.

Aalfredwang0707

Ccheruvatheryvishnu@gmail.com

Fork of Loading and Parsing CSV Data

This example demonstrates loading and parsing CSV data from a remote URL, displaying the file size, row count, and column count. It uses D3 v5’s `d3.csv` method to fetch and parse the CSS Named Colors dataset asynchronously. The code also includes commented-out alternatives using the Fetch API and `d3.csvParse`, illustrating different approaches for handling CSV text. Results appear in a large pre-formatted text element.

Fork of Loading and Parsing CSV Data

This example demonstrates how to load and parse CSV data from a remote URL, displaying the file size, row count, and column count of the CSS Named Colors dataset. The code uses D3 v5’s `d3.csv` method to fetch and parse the data asynchronously, then formats the summary using `d3.csvFormat` and `data.columns`. A commented-out alternative shows parsing via the Fetch API with `async`/`await` and `d3.csvParse`. The results are rendered as large text inside an HTML `<pre>` element.

GGordon Yang

Fork of Loading and Parsing CSV Data

This example demonstrates how to load and parse CSV data using D3. It displays a summary of the CSS Named Colors dataset, including its size in kilobytes, number of rows, and number of columns, in a large monospace text element. The code uses d3.csv to fetch and parse the data, and d3.csvFormat to calculate the byte size. An alternative commented-out approach shows the same task using fetch, async/await, and d3.csvParse. The visualization is minimal, focusing entirely on the data-loading process.

JJoshua-96

Fork of Loading and Parsing CSV Data

This example demonstrates how to load and parse CSV data from a remote URL, displaying the file size, row count, and column count in a large text area. It uses two parallel approaches: the D3.js `d3.csv` method for fetching and parsing, and the native JavaScript `fetch` API combined with `async`/`await` and `d3.csvParse`. The data source is the CSS Named Colors dataset from a GitHub Gist. The visualization itself is minimal, focusing on the process of data ingestion rather than visual encoding.

Mmuwu16

Fork of Loading and Parsing CSV Data

This example demonstrates how to load and parse CSV data, displaying the dataset’s size in kilobytes, number of rows, and columns as large text. It fetches a remote CSV file of CSS named colors using the `fetch` API and `async`/`await`, then parses the text with `d3.csvParse`. The visualization relies on d3 v5 and showcases an alternative to `d3.csv`, highlighting manual text retrieval and parsing.

AAnHaiTrinh