Skip to main content
SimilarExport ZIP
100%

Loading Data

✓ Published136🌍 Public
CCurran Kelleher
Last edited Aug 28, 2025
Created on Jan 18, 2023
Forked from Mouse Follower

This example demonstrates how to load and parse a CSV file in D3.js, displaying the Iris dataset as formatted JSON text in a `<pre>` element. The visualization initially shows a "LOADING" state, then fetches `data.csv` via the Fetch API and parses it using `d3.csvParse`. The code explicitly converts string measurements into numbers for all four numeric columns. State management is handled through a simple `setState` pattern, where the `viz` function checks whether data is loaded, triggers the asynchronous fetch, and re-renders once the parsed array of objects is available.

AI-generated description

Loading a CSV file, the Iris Dataset.

MIT Licensed

Similar vizzes

Loading thumbnail…

Loading Data

This example demonstrates how to load and parse a CSV file in D3.js, displaying the raw parsed data as a stringified JSON object in a `<pre>` element. The visualization uses a state management pattern with a `setState` function to handle asynchronous data loading, initially showing a "LOADING" placeholder. It fetches `data.csv`, parses it with `d3.csvParse`, and converts numeric columns to numbers before updating the display. The Iris flower dataset is used as the data source, with the rendering approach being a simple text-based output rather than a graphical chart.

IIshaChid76
95% match
Loading thumbnail…

Loading Data

This example demonstrates asynchronous data loading by fetching a CSV file of Iris flower measurements and displaying the parsed data as a text preview in the browser. The page initially shows “LOADING” until `fetch` retrieves the file, then `csvParse` converts the raw text into an array of objects. Numeric fields are explicitly converted from strings to numbers with the unary plus operator, and the resulting dataset is rendered inside a `pre` element. The visualization uses a minimal state management pattern with a `setState` function to trigger re-rendering once the data arrives.

LLauren
91% match
Loading thumbnail…

Loading CSV Data

This example demonstrates how to load and parse CSV data with D3.js. It reads the classic Iris dataset, which contains measurements of sepal and petal dimensions for three iris species, and displays the parsed data as a JSON object on the page. The code uses `d3.csv` to fetch the file, applies a row conversion function to coerce numeric fields from strings to numbers, and then logs the result to the console while rendering it in a `<pre>` element for visual inspection.

CCurran Kelleher
90% match
Loading thumbnail…

Loading Data

This example demonstrates the process of loading and parsing external data in D3.js, using the classic Iris flower dataset. The visualization fetches a CSV file with `fetch`, parses it with `d3.csvParse`, and converts numeric columns from strings to numbers. Once the data arrives, the application logs the parsed dataset to the console and updates its state to trigger a re-render, illustrating a unidirectional data flow pattern with D3 v7 and a simple state management approach.

Jjjlaber
90% match
Loading thumbnail…

D3 data loading

This example demonstrates asynchronous data loading in D3 by fetching a CSV file of iris flower measurements (`data.csv`) and displaying the parsed content as a JSON string inside a `<pre>` element. While the request is pending, the text shows “LOADING” before replacing it with the data. Using `d3.csvParse` alongside the `fetch` API, the code converts text into an array of objects, then coerces numeric fields such as `sepal_length` and `petal_width` into numbers with the unary plus operator. The visualization relies on D3 v7 selections with `.join()` to update the DOM, while `index.js` manages a simple state pattern.

SSubhendu Karmakar
89% match
Loading thumbnail…

Loading and Parsing CSV Data

This example demonstrates how to load and parse CSV data using D3’s `csv` function, then display each parsed row as a JSON string in a `pre` element. The visualization uses the `d3-rosetta` library’s `unidirectionalDataFlow` and `createStateField` to manage asynchronous loading states. Data comes from the Iris dataset in `data.csv`, with numeric fields converted via a `parseRow` function. While loading or on error, the chart remains empty; once parsed, rows render instantly.

CCurran Kelleher
89% match
Loading thumbnail…

Fork of Loading Data

This example demonstrates asynchronous data loading with D3 v7 by fetching and parsing the Iris Dataset from a local CSV file. It shows the raw parsed data as a JSON-formatted text preview inside a `<pre>` element, updating the view once the data arrives. The visualization uses `fetch()` to request `data.csv`, converts the response text with `d3.csvParse`, and coerces numeric columns to numbers before storing them in state. The `viz.js` module manages a loading state, initially rendering nothing until the data is processed, then displaying the full dataset structure.

NNatália
89% match
Loading thumbnail…

Fork of Loading Data

This example demonstrates asynchronous data loading in D3, displaying the Iris Dataset as a raw JSON string in a `<pre>` element. The visualization initializes with a loading state, fetches the CSV file via `fetch`, and parses it using `d3.csvParse`. After conversion, numeric columns are cast to numbers before being rendered. The code uses `d3.select` and the `.join()` operation to update the displayed data, showcasing a minimal data-loading and state-management pattern with D3 v7.

Bbillmccabeusa@hotmail.com
88% match