Skip to main content
SimilarExport ZIP
100%

Fork of Blank Slate with Hot Reloading

✓ Published1🌍 Public
CCimmm
Last edited Sep 8, 2024
Created on Sep 8, 2024

This example demonstrates a minimal data-loading workflow using the Iris dataset, fetching the CSV file with d3's `csv` method and logging the parsed result to the browser console. The page itself renders as a blank slate with hot reloading, serving as a starting point for further visualization development. The code relies on the `d3.csv` API to asynchronously parse the comma-separated measurements of sepal and petal dimensions for three iris species, though no visual output is generated yet.

AI-generated description
MIT Licensed

Similar vizzes

Loading thumbnail…

Fork of Blank Slate with Hot Reloading

This example visualizes the classic Iris dataset as a scatter plot, showing petal length against sepal length. Points are colored by iris species according to a categorical scale, with a bespoke color legend positioned in the lower-right corner. The implementation uses D3.js APIs including `scaleLinear`, `scaleOrdinal`, `schemeCategory10`, and `selection.join` to build the chart and its axes declaratively. The code reads CSV data directly and constructs the visualization with the `scatterPlot` module.

Hhuizhi.bt12@nycu.edu.tw
86% match
Loading thumbnail…

Fork of Blank Slate with Hot Reloading

A parallel coordinate plot of the Iris dataset renders 150 flowers across four dimensions (sepal length, sepal width, petal length, petal width) using D3 v7's `d3.scaleLinear` and `d3.scalePoint`. Each line encodes one specimen, colored by species into red, green, and blue via `d3.scaleOrdinal`. Hovering highlights one species by dimming others, while dragging axis labels reorders the dimensions through `d3.drag` with live path updates. The SVG is built from a hash-corrected d3.csv file, though the code contains a typo in the HTML script tag.

Eeyxxr1260@gmail.com
84% match
Loading thumbnail…

Fork of Blank Slate with Hot Reloading

This scatter plot of the Iris dataset uses D3 v7 to visualize four measurements, with dropdown menus to select which features appear on the x- and y-axes. It leverages D3’s `scaleLinear`, `axisBottom`, and `axisLeft` for axes, drawing circles colored by species via `scaleOrdinal` and `schemeCategory10`, plus a legend. The HTML layout holds the SVG and menus, while the JavaScript updates the chart on selection changes.

JJimmy
81% match
Loading thumbnail…

Fork of Fork of Blank Slate with Hot Reloading

This example loads a CSV file from a public gist and presents a data summary, a preview table of the first five rows, and a bar chart showing categorical counts. It uses `d3.csv` to fetch and parse the data, dynamically detects numeric columns, and renders the summary statistics and table into HTML elements. The bar chart is drawn as an SVG using D3’s selection and scale APIs, with all styling applied via CSS.

RRithvik
80% match
Loading thumbnail…

Fork of Loading and Parsing CSV Data

This example demonstrates loading and parsing a CSV file of the Iris dataset. It fetches the remote CSV text using the `fetch` API and then parses it with `d3.csvParse`, logging the resulting tabular data structure to the console. The implementation highlights both the async/await pattern and a commented-out alternative using `d3.csv`. The page itself displays no visual chart, only raw console output, serving as a minimal demonstration of D3’s CSV handling capabilities.

Gginnyching
79% match
Loading thumbnail…

Fork of D3 Starter

This example demonstrates a minimal starting point for a D3 visualization, using the classic Iris flower dataset. It loads the data from a CSV file and logs it to the console, displaying a blank page with centered text. The code utilizes the D3 v7 library, specifically the `csvParse` and `select` APIs, to parse and access the data. The visualization's primary purpose is to show how to set up a basic D3 project and handle external data files.

Fferneyhoughedward@gmail.com
79% 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
78% match
Loading thumbnail…

Fork of Blank Slate with Hot Reloading

This example demonstrates a minimal “Hello World” starting point for the VizHub V3 runtime, which supports continuous hot reloading and interactive widgets. The code loads population data from a CSV file using `d3.csv` and logs it to the console, while a static SVG element is selected with `d3.select`. The visualization itself shows only an empty SVG canvas, with styling applied via external CSS.

MMichael Halim
78% match