AISWARYAMARAPATLA1999

ICE for Plant Species

This visualization shows the hierarchical classification of plant species, branching from plants into non-vascular and vascular categories, then into specific groups like mosses and flowering plants. The code uses the D3.js library’s tree layout to position nodes and diagonal path generator for the connecting links. SVG rendering displays each species as either a circle or diamond shape depending on its numeric value, with link colors varying by the parent level’s assigned color. Text labels accompany each node, and the layout uses fixed-depth positioning to space the hierarchy horizontally.

Apr 6, 2023

CHINA MAP

This example displays a choropleth map of China’s administrative regions, rendered as brown filled paths with white borders on a light yellow background. The visualization loads GeoJSON data for Chinese provinces and projects it using the equirectangular projection from `d3.geoEquirectangular`, with path generation handled by `d3.geoPath`. Users can pan and zoom the map via `d3.zoom`, which transforms the SVG group containing the state paths. The code integrates React, TopoJSON for feature extraction, and D3’s `scaleOrdinal` and `schemeCategory10` for potential color encoding.

Apr 6, 2023

ICE-08 11550685

This example presents an interactive world map using a pink-filled sphere and blue countries with red borders. Hovering over a country highlights it in yellow. The visualization uses D3 v5’s `geoEquirectangular` projection and `geoPath` to render geographic features, while TopoJSON’s `feature` API converts the world-atlas countries-110m.json data into GeoJSON paths. The SVG elements are managed with D3 selections, including `select`, `selectAll`, and `enter`. The map loads the TopoJSON dataset from a CDN and includes basic CSS styling for interactivity.

Apr 6, 2023

ICE-7 Area Chart

This area chart visualizes the number of movie releases per year from 2000 to 2015. The chart uses a yellow filled area beneath a black line, with time-scaled x-axis and linear y-axis, both featuring gridlines. Built with React and D3 v5, the code employs `d3.csv` to load data, `scaleTime` and `scaleLinear` for scales, and `d3.area` with `curveBasis` to generate the smooth area path. Data is fetched from a GitHub gist and rendered as SVG.

Mar 23, 2023

ICE-7 Line Chart

This line chart visualizes the number of movie releases per year from 2000 to 2015, using a red path to highlight trends over time. The visualization is built with D3 v5, employing `scaleTime` for the year-based x-axis, `scaleLinear` for the release counts, and `line` to generate the path. Data is loaded asynchronously from a CSV file hosted on GitHub, with axes labeled and styled using `axisBottom` and `axisLeft`. The SVG rendering includes grid lines, axis labels, and a title, all within a React-based template.

Fork of Pie chart

This example visualizes the top movies and their ratings using a pie chart, with each slice representing a movie and its size proportional to the rating value. The chart renders as an SVG, using D3.js v5's `pie` and `arc` generators to create the segments and a color scale for differentiation. Ratings are loaded from a CSV file via `d3.csv`, and a legend on the right displays each movie's name alongside its corresponding rating value, formatted with `d3.format`.

Fork of Fork of Fork of ICE - 7 Pie Chart Maanas Katta

This example displays a pie chart of the top 10 countries by air pollution deaths in 2020, with white slice labels and a legend showing country names and values. It uses D3 v5, loaded via UNPKG, to generate the SVG chart, with the pie chart layout and arc generator computing the slice geometries. The chart is rendered in an SVG element within a centered HTML page, and the imported D3 modules handle data binding and SVG element creation.

Fork of Fork of Fork of ICE - 7 Pie Chart Maanas Katta

This example visualizes the top 10 countries with the highest number of deaths in 2020 attributed to air pollution. A pie chart displays each country's death count as a colored segment, accompanied by a legend pairing each color with a country name and its corresponding value. The visualization uses D3 v5's `pie`, `arc`, and `scaleOrdinal` APIs to generate and style the SVG paths, with data loaded asynchronously from a CSV file via `d3.csv`. The chart and legend are rendered inside a single SVG element using D3 selections.

Reusable scatter plot with different symbols

This interactive scatter plot visualizes the Iris dataset, mapping petal width and sepal length along the x and y axes while using distinct symbols to represent different species. Built with D3 v6 and React, it renders as an SVG that fills the browser window. The reusable `scatterPlot` component leverages `scaleLinear`, `scaleOrdinal`, `symbols`, and `symbol` to generate the plot, with `axisLeft` and `axisBottom` for the axes. The chart also provides the 100-pixel marks and axis tick styling via CSS.

Fork of ICE-6: Rendering Marks and Channels with React & D3

This example visualizes the basic cost of Netflix subscriptions across different countries using a bar chart. The visualization is built with React and D3, where React handles the component structure and D3 provides the scale functions for mapping data values to pixel positions. A horizontal bar layout displays each country’s monthly price, with the chart rendered inside a React component that leverages d3.scaleBand and d3.scaleLinear for positioning and sizing. The code uses D3’s selection and data join methods to create SVG rectangles, with the cost data hardcoded in the script. The page includes a title and is styled with minimal CSS to keep the chart focused.

Mar 12, 2023

Penguin Data set scatter Plot

A scatter plot of penguin measurements encodes flipper length on the x-axis and body mass on the y-axis, with color distinguishing species (Adelie, Gentoo, and Chinstrap). It also maps bill length and depth to the circles' `rx` and `ry` attributes, creating elliptical marks. Built with D3 v5 (`d3.select`, `d3.scaleLinear`, `d3.axisBottom`, `d3.axisLeft`) inside a React app, it renders to SVG using `d3.csv` to load the PenguinData.csv file. The plot fills the window and includes positioned labels and a title.

Fork of Penguin Data set scatter Plot

This scatter plot visualizes relationships among penguin measurements, with flipper length on the x-axis, body mass on the y-axis, and points colored by species (Adelie, Gentoo, or Chinstrap). The code loads CSV data from a GitHub gist, parses numeric fields, and scales axes using d3.scaleLinear and d3.extent. It renders SVG circles via d3.select, data joins, and join methods, with axes generated by d3.axisLeft and d3.axisBottom. Axis labels and a title are appended as SVG text elements, styled with cursive and times fonts.

Fork of ICE-6: Rendering Marks and Channels with React & D3

This bar chart displays the titles and ratings of 15 movies, fetched from a remote CSV file. Built with React and D3 v5, it renders an SVG with horizontal bars and axes. The code uses `d3.csv` to load and parse data, `d3.scaleBand` for the y-axis, `d3.scaleLinear` for the x-axis, and maps data to SVG `rect` elements for the bars.

Fork of HTML Starter

This example displays the text “Hello HTML!” centered on the page using a CSS class that sets a large font size and text alignment. The page is a minimal HTML document demonstrating the integration of CSS for styling. The code relies solely on the native HTML `<style>` element and standard CSS properties, with no external libraries or JavaScript APIs. The rendering approach is straightforward static HTML, showing how a simple styled message can be presented without any data sources or interactive behavior.

Fork of Fork of ICE-6: Rendering Marks and Channels with React & D3

This visualization displays the basic cost of Netflix subscriptions across 15 countries as a horizontal bar chart. It uses React 16.9 and D3 v5, with React managing component state and D3’s `scaleBand`, `scaleLinear`, and `max` functions for scaling and data processing. The data is loaded via D3’s `csv` method from a GitHub Gist. All marks, including axis ticks and rectangles, are rendered as SVG elements created directly in React’s JSX.

Mar 10, 2023

Fork of Fork of ICE-6: Rendering Marks and Channels with React & D3

This example visualizes the basic cost of Netflix subscriptions across 15 countries using a horizontal bar chart rendered as SVG. It employs React for component management and D3 v5 for data loading and scale construction, specifically using `d3.csv`, `scaleBand`, and `scaleLinear` to map country names and costs. The code builds custom axes with grid lines and tick labels instead of relying on d3's axis generators. Data is fetched from a GitHub-hosted CSV file.

Mar 8, 2023

Fork of ICE-6: Rendering Marks and Channels with React & D3

This bar chart visualizes the basic monthly cost of Netflix subscriptions across 15 countries, using horizontal bars scaled by price. Built with React and D3 v5, the code loads CSV data via `d3.csv`, then uses `scaleBand` for country categories and `scaleLinear` for cost values. The SVG rendering mixes React components for the chart structure with D3 helpers like `xScale.ticks()` for grid lines and axis labels. The visualization highlights pricing disparities, with bars drawn as `rect` elements and axes positioned through D3’s margin convention.

Mar 8, 2023

Fork of ICE-6: Rendering Marks and Channels with React & D3

This bar chart displays the basic cost of Netflix subscriptions across 15 countries, sourced from a CSV file and rendered as an SVG using React 16.9 and D3 v5. It uses `scaleBand` for the categorical country axis and `scaleLinear` for the continuous price axis, with rectangles as marks and position and length as channels. Axes are manually constructed with `axisBottom` and `axisLeft`, and gridlines are drawn directly. The visualization is built declaratively in JSX, with state managed via React hooks.

Mar 8, 2023

ICE5

This example displays metadata for a movie dataset, showing file size, row count, and column count in a text message. The page loads a CSV file from a GitHub gist using D3 v7’s `d3.csv` method, then computes and formats the statistics with `d3.csvFormat`. A CSS background image of movie-themed visuals is applied via `movies.css`, and the dataset link is provided for reference. The visualization is minimal, focusing on data overview rather than graphical representation.

Mar 1, 2023

Fork of Fork of Let's make a face with D3.js!

A smiling face built from SVG shapes animates its eyebrows in a loop. The visualization uses D3.js (v5) to construct and manipulate the face: circles form the head, eyes, and mouth, while rectangles form the eyebrows. The code joins transitions on the eyebrow group to create a repeating up-and-down motion. The rendering is pure SVG, with no external data source, focusing on fundamental DOM manipulation with D3's selection and transition APIs.

Feb 23, 2023