Data Prep

loading and parsing CSV data

This example demonstrates how to load and parse CSV data from a remote URL using D3 v7. It fetches a dataset of CSS named colors via `d3.csv()`, then displays summary statistics in a large HTML `<pre>` element. The output shows the data size in kilobytes, the number of columns, and the number of rows, calculated with `d3.csvFormat()`. The page also includes a separate `fetch()` function for retrieving raw text, though it is not actively used in the final visualization.

BBrian Machado

Loading and Parsing CSV data

This example demonstrates how to load and parse a CSV file from a remote URL using D3.js v7. It fetches a dataset of CSS named colors via `d3.csv`, then displays the file size in kilobytes, the number of rows, and the number of columns in a large HTML `<pre>` element. The visualization relies on `d3.csvFormat` to measure the parsed data’s length, and also includes commented-out alternatives using `fetch` with `d3.csvParse` for comparison.

AAleksandra Timofejeva

Loading and Parsing CSV data

This example demonstrates how to load and parse CSV data from a remote URL using D3 v7. It displays the file size in kilobytes, the number of rows, and the number of columns in a large `<pre>` element. The primary approach uses `d3.csv()` with a promise chain, while commented-out alternatives show `fetch()` with `d3.csvParse()`. The data originates from a GitHub Gist containing CSS color values, and the page also includes an unrelated FPGrowth algorithm example.

CChavaP06

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 as large text. Using D3 v5’s `d3.csv` method, it fetches the CSS Named Colors dataset and formats the results with `d3.csvFormat`. An alternative approach using the Fetch API with `async`/`await` and `d3.csvParse` is included in comments, alongside a commented “pyramid of doom” example. The page renders the summary statistics inside a `<pre>` element within a React framework.

Aa1153724

Loading and Parsing CSV Data

This example demonstrates how to load and parse a CSV file in a web page, displaying the file size, row count, and column count as large text. It fetches a remote CSV of CSS named colors using the Fetch API, then parses the text with `d3.csvParse` from D3 v7. The resulting statistics are written into a `<pre>` element, with the code structured around an asynchronous `fetchText` function and a commented-out alternative using nested promises. The page uses raw HTML, CSS, and JavaScript without any framework.

MMatty Danbury

Loading and Parsing CSV Data

This example demonstrates how to fetch and parse CSV data from a remote URL using D3 v7 and the Fetch API. The page displays a static "Hello HTML!" message, while the main activity occurs in the browser console, where `d3.csvParse` converts the downloaded text into an array of JavaScript objects. The CSV file, sourced from a GitHub gist containing CSS named colors, is retrieved asynchronously via `fetch` and `res.text()`. No visualization is rendered; the focus is solely on the data loading and parsing workflow.

SSerind Joshua McCue

Loading and Parsing CSV Data

This example demonstrates loading and parsing CSV data from a remote URL, displaying the file size, column count, and row count as large text. The code fetches the CSV using the Fetch API, then parses it with `d3.csvParse` to extract metadata. The rendered output is plain text in a `<pre>` element, styled with CSS. The visualization itself is minimal, focusing on the parsing workflow rather than graphical representation. A React-based alternative is also provided, showing mouse tracking with SVG.

PpyDimi

Loading Data

This example demonstrates how to load and inspect a CSV dataset in a web page. It fetches a remote CSV file containing CSS named colors using `d3.csv` with a URL, then displays the file size in kilobytes, the number of rows, and the number of columns in a `<pre>` element. The code also includes commented-out alternatives using the Fetch API and `d3.csvParse` to show different parsing approaches. The visualization is minimal, presenting only textual metadata about the data rather than a graphical chart.

JJosephStalnaker