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 URL, displaying summary statistics about the dataset in a large, readable text format. It uses the `d3.csv` method to fetch and parse the CSS Named Colors dataset, then reports the number of rows, columns, and approximate file size in kilobytes. The code highlights both a promise-based approach with `d3.csv` and an alternative commented-out implementation using `fetch` with async/await and `d3.csvParse`, showcasing different ways to handle data loading in D3 v5 within a React framework.

Aalbb762

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. The code uses d3.csv with a promise to fetch and parse the CSS Named Colors dataset, then formats the statistics with template strings. An alternative approach using the Fetch API with async/await and d3.csvParse is included but commented out, alongside a commented nested-promise example. The result appears as large text in a pre element.

Kktshim@snu.ac.kr

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 loading and parsing CSV data by fetching a dataset of CSS named colors and displaying basic statistics about it. The code uses the Fetch API with async/await to retrieve the data, then parses it with d3.csv, which returns a promise. It computes the file size in kilobytes, row count, and column count from the parsed data, displaying these values in a large pre-formatted text element. The visualization also includes commented-out code showing an alternative approach using d3.csvParse on raw text.

AAlex Gomes

Fork of Loading and Parsing CSV Data

This example demonstrates how to load and parse CSV data from a remote URL, displaying summary statistics about the dataset. The code fetches a CSV file containing CSS named colors and calculates the file size in kilobytes, the number of rows, and the number of columns. It primarily uses `d3.csv` with a promise chain, while commented-out alternatives show the same task using `fetch`, `async`/`await`, and `d3.csvParse`. The results are rendered as large text inside a `<pre>` element, with the D3 library loaded via a CDN.

Sshapak26

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

Fork of Loading and Parsing CSV Data

This example demonstrates the loading and parsing of CSV data from a remote URL containing CSS named colors, displaying the file size, row count, and column count as large text. The visualization uses d3.csv to fetch and parse the data, then d3.csvFormat to calculate its size, with an alternative commented-out approach using the Fetch API and async/await alongside d3.csvParse. The output is rendered into a pre element via JavaScript, showcasing both the modern d3.v5 API and traditional text-based data processing.

RRoberto

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 in large text. It uses D3 v5’s `d3.csv` method to fetch and parse the CSS Named Colors dataset, then computes metrics from the parsed array and its `.columns` property. The code also includes commented-out alternatives using `fetch` with `async/await` and `d3.csvParse`, highlighting different approaches to asynchronous data loading. The rendered output is a simple HTML `<pre>` element updated via the DOM.

CChestnut Sea