nncis

@nncis·12 public vizzes

Stylized bar chart

A stylized bar chart displays the populations of ten countries from 2019 UN Population data, with horizontal bars ranked by country name. The visualization uses React to render SVG elements, including custom axis components and rectangular marks for each bar. D3 utilities like scaleBand, scaleLinear, and csv loading handle data processing and scales. The chart features a teal color scheme, Poppins font, and tooltips showing population values with abbreviated formatting, such as "1.23B".

Oct 10, 2023

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refactored bar chart

This example shows population data for ten countries as a horizontal bar chart. React components render the SVG, while D3 scales and axes handle positioning: `scaleBand` maps country names to vertical bands, and `scaleLinear` maps population values to bar widths. The chart uses data from the UN Population 2019 dataset loaded via `d3.csv`, with custom `AxisBottom`, `AxisLeft`, and `Marks` components.

Oct 3, 2023

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the margin convention

This example shows a horizontal bar chart of the top 10 countries by projected 2020 population, loaded as CSV via D3’s `csv` utility. It demonstrates the margin convention by rendering an SVG with a left offset of 200 pixels, using `scaleBand` for the y-axis and `scaleLinear` for the x-axis, with gridlines from `xScale.ticks()`. React manages the state and renders each `<rect>`, `<line>`, and `<text>` element, while D3 provides the data parsing and scales.

Oct 3, 2023

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Fork of Rendering Data with React & D3

This visualization displays the top 10 most populous countries in 2020 as a horizontal bar chart, using React to render SVG rectangles that scale with each country’s population. It loads CSV data via `d3.csv` and transforms the population column to numeric values with a custom row function. The chart employs `d3.scaleBand` for the country categories and `d3.scaleLinear` for the population values, while React’s `useState` and `useEffect` manage the asynchronous data fetching and rendering state.

Sep 29, 2023

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data about css named colors

This visualization displays all CSS named colors as a circular pie chart, with each color represented as a slice arranged around the center. The data is loaded from a CSV file using `d3.csv` and rendered as SVG paths. React state via `useState` and `useEffect` manages the asynchronous data loading and triggers re-rendering. Each slice is generated using D3's `arc` generator, with the fill color set directly from the hex value in the dataset.

Sep 27, 2023

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Fork of Vega-Lite API Template

This visualization uses the Vega-Lite API with D3 to render a scatterplot of automobile data from the auto-mpg CSV dataset. It plots horsepower against origin, with each point sized and colored by its country of origin, and includes tooltips showing vehicle names. The code registers Vega-Lite with Vega and D3, loads data via d3.csv, and configures axes and label styling for improved readability. The plot fills the entire browser window, with rendering handled through Vega’s SVG view and interactivity powered by vega-tooltip.

Sep 20, 2023

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Loading and Parsing CSV Data

This example demonstrates the process of loading and parsing CSV data from a remote URL, displaying the result as a formatted summary. The visualization presents key metrics about the loaded dataset, including its size in kilobytes, the number of rows, and the number of columns. It uses React's `useState` and `useEffect` hooks to manage asynchronous data loading, while the `d3.csv` function parses the remote CSS named colors file. The message template displays the parsed data statistics using `d3.csvFormat` and accesses the data's `length` and `columns` properties.

Sep 19, 2023

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Fork of Loading and Parsing CSV Data

This example shows how to load and parse CSV data in a browser, displaying basic statistics about the dataset as plain text. It fetches a CSV file containing CSS named colors from a remote URL, then uses d3.csvParse to convert the raw text into an array of objects. The code calculates and displays the file size in kilobytes, the number of data rows, and the number of columns. It relies on the Fetch API with async/await through a custom fetchText function, and manually triggers parsing via the d3.csvParse method.

Sep 19, 2023

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Loading data with react & D3

This example demonstrates how to load and manage data in a React application using D3 utilities, with React state tracking the current mouse position. The visualization renders an SVG circle that follows the cursor as it moves across the screen, with the circle’s center coordinates tied directly to the `mousePosition` state. The code uses React’s `useState` and `useCallback` hooks, along with ReactDOM to mount the component, while D3 is imported for data handling. The SVG viewport is set to 960 by 500 pixels, and the circle radius is fixed at 30 pixels.

Sep 18, 2023

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Mouse Follower

A yellow circle follows the mouse cursor across a fixed 960 by 500 SVG canvas. The example demonstrates real-time mouse tracking with React 16.9.0, using the `useState` and `useCallback` hooks to manage cursor coordinates. The `onMouseMove` event on the SVG element updates the circle’s `cx` and `cy` attributes, causing it to smoothly track the pointer. The code renders a single SVG circle with no data source, purely illustrating interactive state updates in a React-driven visualization.

Sep 18, 2023

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Fork of HTML Starter

This example demonstrates a minimal HTML page that fetches and logs a CSV file of CSS named colors from a GitHub gist. It uses the Fetch API in an async/await pattern to retrieve the text and output it to the browser console. The page also includes a large styled greeting message via CSS, while the JavaScript handles the data request. The code shows both an active async/await implementation and a commented-out alternative using promise chaining.

Sep 15, 2023

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Fork of Hello HTML

This example displays a grid of 18 randomly generated cartoon faces, each composed of a yellow circular background, two eyes, and a mouth. The faces are rendered as SVG elements using React and D3 v7, with the mouth shape created through D3’s `arc` generator. The layout is produced by mapping over a D3 `range` array, while each facial feature’s dimensions are individually randomized on every render.

Sep 11, 2023