lottery mega millions

100%

lottery mega millions

✓ Published0🌍 Public

Last edited Sep 17, 2025

Created on Sep 17, 2025

This visualization displays the raw values of the Iris dataset as a JSON stream, loading the data from a CSV file and converting its numeric fields. The code uses D3’s `select` and `csvParse` to fetch and parse the data, then renders it via a `join` operation into a `pre` element. It demonstrates a minimal state-based data-loading pattern, transitioning from an undefined state to a 'LOADING' state before displaying the parsed array of objects.

AI-generated description

MIT Licensed

Similar vizzes

Loading thumbnail…

world-happiness-data

This example loads the Iris dataset from a CSV file and displays it as raw JSON text in a `<pre>` element. The visualization uses d3.csvParse to convert the CSV string into an array of objects, then coerces numeric columns to numbers. It demonstrates a state management pattern with d3-selection’s select and join methods, where data is asynchronously fetched and rendered after a loading state. The code shows only text output, not a graphical chart.

Ccsabavath@wpi.edu

74% match

Loading thumbnail…

The Iris Dataset

This example presents a minimal D3.js visualization that loads the classic Iris flower dataset from a CSV file (iris.csv) and displays its contents as raw, formatted JSON text on the page. Using the `d3.csv` method with a type conversion function, the code converts the numeric measurement columns to numbers before rendering the complete dataset structure with `JSON.stringify`. The simple output is intended as a starting point for testing data-loading workflows, showcasing 150 rows of sepal and petal measurements across three iris species from the UCI Machine Learning Repository.

IIoTeacher

73% 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

73% 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

73% match

Loading thumbnail…

Dataset1_crypto_analysis

This example loads the classic Iris flower dataset and displays it as raw JSON text. The visualization initially shows a loading state before fetching the CSV file via `fetch` and parsing it with `csvParse`. The code then converts the numeric measurement strings to numbers and updates the display through a state management pattern using `setState`. The interface is built with `d3.select` and a join operation to render the JSON-serialized data into the container.

BBismark Kofi Owusu Sarfo

72% match

Loading thumbnail…

D3 data transformation

This example demonstrates a simple data-loading and transformation workflow using D3. It fetches a CSV file containing the classic Iris dataset and uses `d3.csvParse` to convert the raw text into an array of objects, subsequently coercing the numeric measurement columns to numbers. The resulting parsed data is displayed as formatted JSON inside a `<pre>` element. The visualization uses a minimal state management pattern, with a `setState` callback triggering re-renders, and leverages D3’s `select` and `join` for DOM updates.

SSubhendu Karmakar

72% 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

72% 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

71% match