Fork of Loading Data

100%

Fork of Loading Data

✓ Published0🌍 Public

Last edited Nov 11, 2024

Created on Nov 11, 2024

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.

AI-generated description

Loading a CSV file, the Iris Dataset.

MIT Licensed

Similar vizzes

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

95% match

Loading thumbnail…

Fork of Loading Data

This example demonstrates asynchronous data loading in a D3.js visualization. The code fetches a CSV file containing the classic Iris flower dataset, parses it, and displays the raw JSON-formatted data prominently as the primary output. The visualization progresses through distinct states—starting with undefined, transitioning to a "LOADING" message, and finally populating with the parsed array of objects. It uses D3's `select`, `join`, `csvParse`, and a state management pattern with `setState` to control the rendering and handle the fetch-and-parse pipeline.

Sskasliwal@wpi.edu

93% match

Loading thumbnail…

Fork of Loading CSV

This example demonstrates how to load and display a CSV dataset using D3.js. It fetches the Iris Dataset from a remote URL and renders the raw data as formatted JSON text on the page. The visualization first uses D3’s `csv` function to asynchronously load the data, then chains a `.then()` callback to append a `<pre>` element to the body, converting the parsed data to a readable JSON string with `JSON.stringify`. The code relies on D3 v5’s `select` and `csv` APIs, showing a minimal workflow for ingesting tabular data and presenting it in the browser without any charting or interactive elements.

MM Hema

89% match

Loading thumbnail…

Fork of Loading CSV

This example demonstrates how to load a CSV dataset and display its contents as raw JSON text on the page. It fetches the Iris Dataset from a remote GitHub URL using the `csv` function from D3 v5, then formats the parsed data with `JSON.stringify` for readability. The code appends a `<pre>` element to the document body using `select` and `append`, showing the structured array of objects that results from parsing the CSV. The visualization is minimal, focusing purely on data loading and inspection.

Yyasmeenha

89% match

Loading thumbnail…

Fork of Loading Data practice

This example demonstrates a unidirectional data flow pattern: a circle follows the mouse cursor while loading and displaying the Iris dataset. The visualization first fetches `data.csv` containing sepal and petal measurements, parses it with `csvParse`, and converts the numeric string values to numbers. A `pre` element displays the JSON-formatted state data, which transitions from a string `"loading"` to the complete dataset. The code uses D3 v7's `select` and `join` APIs to manage the DOM and implements explicit `setState`/`render` functions to maintain predictable one-way data flow.

KKhatera Alizada

89% match

Loading thumbnail…

Loading Data

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.

CCurran Kelleher

88% match

Loading thumbnail…

Fork of Data transformation

This example demonstrates the loading and parsing of the Iris Dataset from a CSV file, displaying the raw tabular data as formatted JSON text. The visualization initially shows a "LOADING" state before fetching the CSV, then uses `d3.csvParse` to convert the text into an array of objects, explicitly coercing the four measurement columns to numbers. The rendering is handled by a simple D3 data join that updates a `<pre>` element with the parsed data, driven by a state management pattern where `setState` triggers re-rendering. The Iris Dataset contains 150 samples of sepal and petal measurements across three iris species.

KKhatera Alizada

88% match

Loading thumbnail…

Fork of Loading Data

This example demonstrates loading and parsing the Iris Dataset from a CSV file using D3’s `csvParse` function, then rendering a single circle at a fixed position with the `scatterPlot` module. The visualization initializes with a loading state, fetches the data asynchronously, converts numerical columns to numbers, and triggers a re-render once data arrives. It uses D3 v7 selections and joins to manage the SVG and circle elements, with a minimal UI showing the data-loading process.

Ffloraho401

88% match