Fork of Loading and Parsing CSV Data

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 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 demonstrates how to load and parse CSV data in a web page, displaying the file size, row count, and column count of the CSS Named Colors dataset. It uses d3.v5's `d3.csv` method to fetch and parse the data from a remote URL, then applies `d3.csvFormat` and array properties to summarize the contents. The interface is minimal, showing the statistics in a large `<pre>` element styled with CSS. The code also includes commented-out alternatives using `fetch`, `async`/`await`, and `d3.csvParse` for comparison.

NNigel

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 demonstrates how to load and parse CSV data from a remote URL, displaying a summary of the dataset’s size in kilobytes, number of columns, and number of rows. It uses the D3.js v5 library, specifically the `d3.csv()` function for fetching and parsing, and `d3.csvFormat()` to measure the data size. The parsed data comes from a CSS Named Colors dataset hosted as a gist. The result is rendered as plain text inside an HTML `<pre>` element.

AAmine HAMOU

Fork of Loading and Parsing CSV Data

This example demonstrates loading and parsing CSV data using D3 v5, displaying summary statistics about the dataset in a large HTML `<pre>` element. The visualization shows the file size in kilobytes, the number of rows, and the number of columns from a CSV file containing CSS named colors. The code uses `d3.csv` to fetch and parse the remote CSV URL, then `d3.csvFormat` to calculate the data’s size. The resulting text output updates the page via the Document Object Model’s `textContent` property.

LLawrence Liu

Fork of Loading and Parsing CSV Data

This example demonstrates loading and parsing a CSV file containing CSS named colors. The visualization itself is minimal, displaying text statistics about the dataset: its size in kilobytes, the number of rows, and the number of columns. The code uses the D3.js library (v5) method `d3.csv` to fetch the remote CSV, then `d3.csvFormat` and the `data.columns` property to compute these metrics. The results are rendered as plain text in an HTML `<pre>` element.

AAnu Wat

Fork of Loading and Parsing CSV Data

This example shows the result of loading and parsing a CSV file containing CSS named colors. The interface displays three summary statistics: the approximate file size in kilobytes, the number of data rows, and the number of columns. It uses D3 v5’s `d3.csv` function to fetch the remote resource and parse it, then leverages the `d3.csvFormat` method to calculate the raw character count. The parsed data object’s `length` and `columns` properties provide the row and column counts, which are rendered inside an HTML `<pre>` element.

Bbhavani44