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achalasam

@achalasam·17 public vizzes

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ICE 8 India

This example presents a map of India, rendered as a collection of purple SVG paths on a full-screen canvas. The visualization loads geographic data from a GitHub-hosted TopoJSON file and converts it into GeoJSON features using the TopoJSON `feature` API. The map is drawn using D3’s `geoMercator` projection and `geoPath` generator, invoked within a React component structure. The code demonstrates an integration of React for component management, D3 v5 for geographic projection and path generation, and a minimal HTML/CSS setup for display.

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Social Network Graph ICE-8

A social network graph visualizes relationships between people, with nodes representing individuals and directed links showing "Friend with" connections. The graph uses a force-directed layout, where nodes are positioned through physical simulation and can be dragged interactively. Built with React and D3 v6, it employs `d3.forceSimulation` for layout, `d3.forceLink`, `d3.forceManyBody`, and `d3.forceCollide` for physical forces, and `d3.drag` for user interaction. The visualization renders as SVG, with node labels and hover effects that highlight connected nodes.

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Family Tree

This visualization presents a family tree as an interactive, animated SVG diagram built with React and D3.v3, using the `d3.layout.tree` API to compute the hierarchical layout. Color-coded nodes (distinguished by `type` values) represent different family members, and red links with directional arrows show parent-child relationships. Users can click nodes and zoom the entire tree via a zoom behavior. Data is loaded asynchronously from the `family-data.json` source, and the tree dynamically resizes its SVG canvas based on the maximum depth and breadth of the loaded data.

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ICE-8 World Map

This is a world map visualization rendered with SVG, showing countries as purple regions with pink borders against a light yellow sphere. The map uses a natural Earth projection and loads geographic data from the World Atlas JSON file. The code imports `geoPath` and `geoNaturalEarth1` from d3, along with the `feature` function from topojson, to generate and project the country boundaries onto the SVG canvas.

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Cricket Runs Analysis

This interactive bar chart visualizes cricket runs scored by different players each month from January through May. The visualization uses d3.x3d to render a 3D multi-series bar chart, with each player’s monthly performance represented as a separate series. The code loads player data from a CSV file using d3.csv, parses the values into the required format, and feeds them into the d3.x3d.chart.barChartMultiSeries function. The chart is displayed within an HTML page that imports D3 v5, d3-3d, and x3dom libraries to support the three-dimensional rendering.

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Bonus ICE - 3D Bar chart

This 3D bar chart visualizes the runs scored by seven cricketers across five months (January through May), using a three-dimensional perspective to compare performance over time. The chart employs Highcharts with the highcharts-3d extension, configuring the chart type as 'column' with 3D options for depth, alpha, beta, and view distance. Each month is represented as a separate series with stacked, grouped columns, while the x-axis lists player names and the y-axis displays runs scored. The z-axis denotes months, and colors distinguish each series within the interactive HTML page.

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Cricketers Match Analyis

This example uses Plotly to render a 3D scatter plot of cricket player performance, comparing the number of sixes, fours, and matches played for each player. The data is loaded from a remote CSV file using D3’s `d3.csv` function, then unpacked into arrays for the x, y, and z axes. Each marker is a green diamond, with axes labeled accordingly and custom margins applied. The visualization is embedded in a simple HTML page with Plotly’s `Plotly.newPlot` method.

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Untitled

This example builds an interactive bar chart from tabular sales data using D3.js v2 and React. It displays the data as vertical bars with drop shadows, using ordinal and linear scales for positioning and height. The SVG rendering includes axis labels, tick formatting that maps to captions, and a y-axis scaled to the maximum value. The chart is embedded in a styled container and updates programmatically via a `Plot()` function when the page loads.

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ice-7 Q1 "Resuable Scatter Plot"

This example presents a reusable scatter plot that visualizes cricket statistics over time, cycling the x-axis through different numeric columns every two seconds. Built with D3 v6, it uses `scaleLinear`, `scaleOrdinal`, and `symbol` to render players as distinct shapes, with the SVG updating via `svg.call(plot)` to retrigger the chart. Data loads from a CSV file containing yearly runs, outs, and fours, and the chart supports configurable margins, radius, and accessor functions for flexibility. The implementation follows Mike Bostock’s “Towards Reusable Charts” pattern with a closure-based API.

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Fork for area chart

This example visualizes the runs scored by Rohit Sharma from 2007 to 2021, combining a smooth line chart with a filled area beneath it. The SVG rendering uses d3.scaleTime and d3.scaleLinear to map years and run counts, while d3.line and d3.area generators with curveBasis create the curved paths. Axis ticks are formatted with d3.format and styled via CSS classes, with data parsed from a CSV file loaded through d3.csv.

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line chart

This line chart shows Rohit Sharma’s runs per year from 2007 to 2021. The SVG visualization uses D3 v5 with React, scaling time on the x-axis and linear values on the y-axis via `scaleTime` and `scaleLinear`. Axes are rendered with `axisBottom` and `axisLeft`, while the data line is drawn using `line`. The CSV dataset is loaded asynchronously with `csv`, and the chart includes gridlines and axis labels.

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ICE - 7 Pie Chart

This pie chart displays the top 10 countries by COVID-19 deaths, with each slice labeled with the death count in thousands and accompanied by a legend listing country names and values. The visualization uses D3 v5 (including `d3.pie`, `d3.arc`, and `d3.scaleOrdinal`) to compute arcs and colors, rendering SVG elements dynamically. Data is loaded from a CSV via `d3.csv` and sorted before selecting the first ten rows, all within a React-compatible setup.

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ice-7

This example shows a line chart of automobile sales in India from 1999 to 2012, with years on the x-axis and electronic sales figures on the y-axis. The chart uses D3 v7’s `scaleTime`, `scaleLinear`, `axisBottom`, `axisLeft`, and `line` to render the path and axes, with data loaded via `csv` from a GitHub gist. A title and axis labels are added as SVG text, and gridlines appear as ticks extending across the plot area.

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Scatter plot for iris data set

This visualization displays the classic Iris dataset as a scatter plot, mapping petal length on the x-axis and sepal length on the y-axis. Each point represents an individual flower, colored by species (setosa, versicolor, or virginica) using a custom marker function. The code loads data via `d3.csv` from a GitHub gist, parses numeric fields, and renders circles with `d3.selectAll` and `.join()`. Axes are generated with `d3.axisLeft` and `d3.axisBottom`, while `d3.scaleLinear` and `d3.extent` set the scales to the data domain.

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Data Visuliazation ICE-6

This example shows the top 10 car models by sales in thousands, rendered as a horizontal bar chart. The visualization loads CSV data from a GitHub gist, slices the first 10 rows, and maps the `Sales_in_thousands` field to bar widths using `d3.scaleLinear`, while `d3.scaleBand` positions the model names along the y-axis. React hooks (`useState`, `useEffect`) manage the asynchronous data loading, and the SVG elements (rectangles, axes, and tick labels) are generated declaratively within a React component, with styling controlled by inline attributes and CSS.

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Data Visualization ICE5

This example presents a web page that uses D3.js v7.3.0 to load and summarize a CSV file from a GitHub Gist. It displays the file’s size in kilobytes, the number of rows, and the number of columns in a `<pre>` element. The page also includes two SVG images of a rocket and a cricket, using them as visual elements alongside the text. The code uses the `d3.csv` API to fetch the data and `d3.csvFormat` to calculate the data size, while CSS flexbox controls the image layout.

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face

This example displays a stylized smiley face rendered as an SVG graphic, featuring a pink circular head, green eyes with pupils, and a black arc-shaped mouth. Built with React and D3 v7, it uses the `d3.arc()` API to generate the mouth path, while positioning all other facial elements—including circles, ellipses, and lines—through hard-coded coordinates. The face is centered within a fixed 900×500 viewport, with facial features arranged symmetrically to create a playful, static illustration.