P

P Manisha

@Manishaaaaaaa·18 public vizzes

Loading thumbnail…

World Map with Population

This example displays a world map choropleth of GDP data, with each country colored according to its economic value. It uses D3 v7 and TopoJSON to load world geography, projecting the map with the `d3.geoNaturalEarth1` projection and rendering countries as SVG paths via `d3.geoPath`. GDP values are fetched from a CSV file, matched to countries through flexible column-name heuristics, and visualized with a color scale. A hover tooltip provides country-specific details, while the map includes a legend for interpreting the color encoding.

Loading thumbnail…

Network Graph

This network graph visualizes the relationships between three authors and three papers, with blue circles representing authors, orange circles representing papers, and gray lines indicating authorship connections. The code uses D3.js v7’s `d3.forceSimulation` to apply a force-directed layout with `forceLink`, `forceManyBody`, and `forceCenter` forces, causing nodes to arrange dynamically. Positions update on each simulation tick, adjusting line coordinates and circle/text placement in the SVG. Labels display each node’s name above its circle, and the layout stabilizes as the simulation runs.

Loading thumbnail…

Tree

This tree visualization displays a five-generation family hierarchy, with each generation distinguished by both color and node shape, ranging from circles for the root and parents to squares, diamonds, and triangles for subsequent descendants. The D3.js code uses the `d3.stratify()` and `d3.tree()` APIs to convert flat data into a hierarchical structure and compute the layout, drawing links as lines and rendering nodes as SVG shapes within a white-bordered chart. A legend above the chart clarifies the mapping of generation to shape and color.

Loading thumbnail…

Tree

A hierarchical tree diagram displays the structure of programming languages, grouped into Web, System, and Data categories. The visualization uses a static dataset defined in JavaScript. D3.js v7 with an SVG rendering approach draws the graph, employing `d3.hierarchy` and `d3.tree` to compute the layout. Nodes are represented as colored circles, color-coded by depth using `d3.scaleOrdinal` with `d3.schemeCategory10`, while links and text labels are appended via D3's data-join methods. The tree is oriented horizontally, placing parent-child connections left-to-right.

Loading thumbnail…

map

This visualization displays a world map where each country is colored according to its population using a sequential yellow-orange-red color scale. Population data is loaded from a CSV file and merged with country geometries from the world-atlas TopoJSON dataset. The map uses a Mercator projection via d3.geoMercator and renders paths with d3.geoPath, while hovering over a country reveals its name and population in a tooltip. Missing data appears gray, and the SVG canvas includes a light blue background.

Loading thumbnail…

Reusable Scatter Plot (Car Engine)

This scatter plot visualizes the relationship between engine size and fuel efficiency (MPG) using a dataset of car engines. The visualization shows individual data points as blue circles, with clear axis labels displaying the measured variables. Built with D3.js (v7), the implementation uses `d3.csv` to load data from a GitHub-hosted CSV file, `d3.scaleLinear` for axis scaling, and `d3.axisLeft` and `d3.axisBottom` to render the chart axes. The SVG-based rendering is encapsulated in a reusable `ScatterPlot` function that accepts configurable dimensions, margins, and data value accessors, allowing for flexible reuse across different datasets.

Loading thumbnail…

AREA CHART

This area chart displays monthly revenue trends from a CSV dataset, filling the area beneath the line with light steelblue and outlining it in steelblue. The visualization uses D3 v7’s `d3.area()` generator, with a `scalePoint` for months on the x-axis and a `scaleLinear` for revenue on the y-axis. Axes are rendered using `d3.axisLeft` and `d3.axisBottom`, with labels added for both dimensions. The chart is drawn as an SVG element within a `div` container, with the data loaded asynchronously from a GitHub-hosted CSV file.

Loading thumbnail…

LINE CHART

This line chart displays monthly revenue trends over time, with each data point marked by a circle and connected by a steelblue line. The visualization uses D3 v7’s `d3.scalePoint` for the categorical month axis, `d3.scaleLinear` for the revenue scale, and `d3.line` to generate the path. Data is loaded asynchronously from a CSV file via `d3.csv`, and rendered as SVG with axis labels and gridlines.

Loading thumbnail…

pie_sales

This pie chart visualizes product sales from a CSV file, displaying each product’s share as a colored slice with labels positioned at each slice’s centroid. The chart uses d3.pie() to compute arc angles and d3.arc() to render the SVG paths, with a d3.scaleOrdinal and d3.schemeCategory10 providing color encoding. A legend below the chart lists each product and its corresponding sales value, generated from the same loaded data. The visualization is built with D3 v7 and rendered as inline SVG within an HTML container.

Loading thumbnail…

Reusable Scatter Plot

This scatter plot from the D3.js gallery visualizes the relationship between math and reading scores for individual students, with each point positioned by d3.scaleLinear scales and rendered as an SVG circle. The reusable ScatterPlot function, exported from scatterPlot.js, accepts data, accessor functions, and margin/width/height parameters to generate axes via d3.axisLeft and d3.axisBottom. It loads student performance data from a GitHub-hosted CSV file, parsing numeric fields before plotting steelblue circles, with axis labels added using SVG text elements.

Loading thumbnail…

StudentPerformanceScatter

This scatter plot visualizes the relationship between math and reading scores for a student performance dataset. Each circle represents a student, positioned by their math score on the x-axis and reading score on the y-axis, with steelblue marks at a radius of five units. The example uses D3’s `scaleLinear`, `extent`, and `axisBottom`/`axisLeft` APIs to construct the coordinate system and axes. Data is loaded remotely from a GitHub-hosted CSV file using `d3-fetch`’s `csv` function, with numeric parsing applied to the relevant score columns before rendering to an SVG canvas.

Loading thumbnail…

ICE 6

This visualization displays the characteristics of Fisher's Iris dataset, comparing sepal length and width across three species. The scatter plot maps sepal dimensions on the x and y axes, with each species indicated by a distinct color. Rendered as an SVG, it uses d3.scaleLinear and d3.scaleOrdinal to construct the plot and color scale. Interactive legend hovering highlights points of a selected species in full opacity while fading others, implementing fade effects through D3's join and raise methods.

Loading thumbnail…

line chart

This line chart visualizes Seattle weather trends in 2016, showing maximum, mean, and minimum temperatures over the first 200 days using three colored lines. The chart combines a multi-series line graph with overlaid bars representing the mean temperature. Built with D3 v7, the code loads CSV data and uses `d3.line()`, `d3.scaleLinear()`, and `d3.axisBottom()` to render the SVG visualization, including axes, labels, and a legend for temperature series.

Loading thumbnail…

ICE-6 Scatter Plot

This scatter plot visualizes the relationship between math and reading scores from the StudentsPerformance dataset. It uses d3.csv to load the data and d3.scaleLinear to map score values to SVG circle positions. The chart is rendered entirely in SVG using d3.v7, with circles, axes, labels, and a title added programmatically through d3.select and append methods.

Loading thumbnail…

EV_Sales_ICE_Submission

This visualization displays EV sales data by brand and year. It loads CSV data from a GitHub gist and presents a summary table of all records alongside an SVG bar chart showing total units sold for Tesla, Nissan, and Chevrolet. The bar chart uses D3 v7 within a React framework, with axes, gridlines, and a title rendered as scalable vector graphics. Population-by-country data is also loaded separately, with a bar chart showing the top countries by population.

Loading thumbnail…

Fork of ICE6

This visualization displays the classic Iris dataset as a scatter plot, comparing sepal length against sepal width for three species of iris flowers, with an interactive legend that highlights each species on hover. The plot uses D3.js scales (scaleLinear, scaleOrdinal), axes (axisBottom, axisLeft), and a ResizeObserver to make the visualization responsive. Points are rendered as SVG circles with a BBC-inspired color theme, while the legend smoothly fades non-hovered species to 20% opacity. Data is loaded asynchronously from a remote CSV file using D3’s csv parser.

Loading thumbnail…

ICE6

This scatter plot visualizes the Iris dataset, comparing sepal length and width across three species using a BBC-inspired color palette. Built with D3 v7, it uses `scaleLinear` for axes, `scaleOrdinal` for categorical coloring, and interactive legend hover effects that fade non-selected species. The visualization loads data via `d3.csv` from a GitHub gist and includes a responsive `ResizeObserver` for dynamic resizing.

Loading thumbnail…

ICE6

A React-based bar chart visualizes letter frequencies from a CSV dataset. Built with D3 v7, it uses `scaleBand` for the x-axis and `scaleLinear` for the y-axis, rendering bars with rounded corners and a teal fill. Clicking a bar toggles its selection, highlighting it while dimming others. The chart includes axes with gridlines, titles, and responsive sizing via a `ResizeObserver`.