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Nithish Kumar

@Nithish-kumar-11·20 public vizzes

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USA Country Map

Choropleth map of the United States uses SVG paths to display all fifty states from TopoJSON data, with state boundaries rendered as black strokes. The visualization employs d3.geoPath with the geoAlbersUsaTerritories projection to convert geographic coordinates into screen positions. Hovering over any state changes its fill color from green to orange through CSS :hover rules. The React component loads the geographic topology asynchronously via d3.json and processes it with topojson.feature and topojson.mesh utilities.

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India Map

This example displays a choropleth map of India’s states, with each state filled by a distinct color from d3’s `scaleOrdinal` and `schemeCategory10`. Using topojson data loaded from a remote GitHub repository, the code projects the geometry with `d3.geoMercator` and renders it as SVG paths via `d3.geoPath`. State names are positioned at each polygon’s centroid, while hover effects and a light pink stroke are defined in the accompanying CSS. The visualization relies on the D3 v5 library and topojson for geographic feature extraction.

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networks ICE 8

This social network graph visualizes a personal friendship network, using a force-directed layout to position ten individuals. Nodes are rendered as cyan circles with labels, and links between friends are shown as lines with arrow markers. The visualization is built with D3 v6, using `d3.forceSimulation` with link, many-body charge, collision, and center forces to arrange the network. Node dragging is enabled via D3’s drag interaction, and hovering highlights a node with a thicker stroke. The data comes from a JSON file containing node and link definitions.

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ICE-8 Animals tree Chart

This interactive tree chart visualizes a hierarchical classification of animals, branching from a central “Animal” node into mammals, reptiles, and birds, with leaf nodes for specific species. Each node is rendered as a circle whose size reflects a numeric value, while stroke and fill colors encode categorical attributes from the data. Built with D3 v5 and React, the visualization uses `d3.hierarchy` and `d3.tree` to compute node positions, draws curved links via SVG paths with `d3.select`, and styles circles and text labels directly in an SVG canvas.

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Social Network Graph --> ICE-8

This example visualizes a social network as a force-directed graph, showing friend relationships among a group of people. The nodes, rendered as large cyan circles with labels, are positioned using `d3.forceSimulation` with link, charge, collision, and center forces. The data, loaded from a JSON file, defines nodes and links with relationship attributes. The graph uses SVG elements, with markers indicating link direction. Users can drag nodes to reposition them, and hovering highlights a node by thickening its stroke via CSS classes.

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My group of friends ICE 8

A force-directed graph visualizes a social network of ten friends, showing connections between individuals like Nithish, Anjani, and Vishal. Nodes are rendered as cyan circles with labeled text, while directed links with arrowheads indicate friend relationships. The layout is computed using `d3.forceSimulation` with `d3.forceLink`, `d3.forceManyBody`, `d3.forceCollide`, and `d3.forceCenter`. Nodes are draggable via D3's `drag` behavior, and hovering highlights a node by expanding its stroke. The data comes from a JSON file and is displayed as an SVG using D3 v6.

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Let's make a map with D3.js!

This example displays a world map using the Natural Earth projection, with countries rendered as light green SVG paths and the ocean as a blue sphere. It loads geographic data from the World Atlas TopoJSON file, converting it to GeoJSON with the topojson `feature` function. The code uses D3 v5’s `geoNaturalEarth1` projection, `geoPath` for path generation, and `selectAll` to bind country features to SVG elements.

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Reusable scatter plot with different symbols

This example presents a reusable scatter plot of the Iris Dataset, encoding sepal length against petal width. Each species is visually distinguished by a different D3 symbol, with axes scaled using `d3.scaleLinear`. The plot is built as a custom charting function that chains configurable accessors for data, dimensions, and margins. It leverages `d3.scaleOrdinal` to map species to `d3.symbols`, and renders SVG paths via `d3.symbol` and the `d3.axisBottom` and `d3.axisLeft` components.

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Area Graph of sales in Automobile

This area graph visualizes automobile sales from 2000 to 2010, with the y-axis labeled “Sales” and the x-axis showing years. The data, sourced from a CSV file, is rendered as a smooth green filled area using d3.area with curveBasis. The chart uses d3.scaleTime and d3.scaleLinear for axes, and d3.axisBottom and d3.axisLeft for ticks. Axis labels and a title are added via SVG text elements.

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Line chart of sales

This line chart shows annual automobile sales from 2000 to 2010, with the year on the x-axis and sales figures on the y-axis. The visualization uses d3.scaleTime and d3.scaleLinear to map the data, while d3.line generates the path that traces the sales trend. Data is loaded from a GitHub gist CSV file. The chart includes labeled axes, a title, and gridlines styled via CSS, with the line path rendered in SVG as a green stroke.

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Line Chart

This line chart displays US auto sales from 2005 to 2022, plotting annual sales figures against time. The visualization is built using D3 v5, employing `scaleTime` and `scaleLinear` for the axes, with `axisBottom` and `axisLeft` generating the labeled ticks. A red path, created by the `line` generator, connects the data points, which are loaded via `csv` from a GitHub gist. The SVG rendering includes axis labels and a title, all styled through external CSS.

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Pie Chart of Covid 19 Deaths

This pie chart visualizes COVID-19 deaths by country, with each slice’s size proportional to the total death count and labeled in thousands. The chart uses D3 v5’s `pie` and `arc` generators to compute and draw the segments, `scaleOrdinal` to assign categorical colors, and `format` to abbreviate numeric labels. A legend lists each country alongside its corresponding color and value. Data is loaded asynchronously from a CSV file hosted on GitHub via `d3.csv`, and all graphics are rendered as SVG elements within a fixed 960×500 viewport.

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Reusable D3 Scatter Plot

This example demonstrates a reusable scatter plot of the Iris dataset, cycling through different flower measurements every two seconds to show the relationship between variables. Built with D3 v6, it uses the reusable chart pattern with a closure-based `scatterPlot()` function exposing getter-setter methods for width, height, data, margins, and scales. The plot renders SVG circles with `d3.scaleLinear` for axes and `axisLeft`/`axisBottom` for ticks, updating via `selection.join()`. Data is loaded from a CSV file using `d3.csv`, while the animation is driven by `setInterval`, calling the plot again with a new x-value mapping.

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Scatter Plot of Penguin Dataset

This scatter plot displays the penguin dataset, mapping flipper length and body mass with colored circles that represent species (yellow for Adelie, green for Gentoo, brown for Chinstrap). It also encodes bill length and bill depth as circle radii, adding a second dimension of comparison. Built with React and d3.v5, the example loads CSV data via `csv`, scales with `scaleLinear`, and renders SVG circles with axes from `axisLeft` and `axisBottom`. Axis labels and a title are added manually, with styling applied through CSS.

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scatter plot of penguin dataset

This scatter plot visualizes the Palmer Penguins dataset, showing the relationship between sepal length and petal length. The visualization uses D3 v7 with a linear scale for both axes, rendering circles with a radius of 10 pixels for each data point. The axes are generated using D3’s `axisLeft` and `axisBottom` functions, with labels for both dimensions. Data is loaded from a CSV file and parsed using `csvParse`, with numeric fields converted to numbers before plotting.

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

The visualization displays the top 15 countries by COVID-19 deaths using a horizontal bar chart, with each bar’s length encoded by the `Deaths` value on a linear scale. The chart fetches its data from a CSV file and renders a static SVG. It uses the `d3.scaleBand` for y-axis positioning, `d3.scaleLinear` for the x-axis, and `d3.svg` icons to draw axis ticks and labels. The React component manages state with `useState` and `useEffect`, and the bars and axes are generated by mapping over the data within an SVG `<g>` element.

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ICE-6 Nithish Kumar

This horizontal bar chart displays the top cosmetic products by revenue, sourced from a CSV file. The visualization uses D3 v5’s `scaleLinear`, `scaleBand`, `axisLeft`, and `axisBottom` to map revenue values and product names, with SVG rectangles representing the bars. Axes are customized by removing domain lines and applying a tick formatter that converts large numbers to abbreviated units. The data is loaded via `d3.csv` and rendered with margins and labels for the title and x-axis.

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ICE-6

This bar chart displays COVID-19 deaths by country, ranking the top nations based on their reported death tolls. The visualization uses a horizontal bar layout with red rectangles, where the x-axis represents death counts and the y-axis lists country names. The code imports D3 v5 functions including `scaleLinear`, `scaleBand`, `axisLeft`, and `axisBottom` to construct the chart, with custom tick formatting that converts large numbers into abbreviated values. The data is loaded via `d3.csv` from an empty URL, so the chart renders without actual data in its current state.

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

This example displays a bar chart of the top 15 Instagram influencers by follower count, using horizontal bars encoded by channel name on the y-axis and follower totals on the x-axis. Built with React and D3 v5, it loads CSV data from a GitHub gist via `d3.csv` and renders SVG marks and channels using `scaleBand`, `scaleLinear`, and `rect` elements. Axes are drawn manually with `ticks` and grid lines, all managed through React's `useState` and `useEffect` hooks.

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ICE5

This interactive webpage displays the top Instagram influencers, presenting metadata about the dataset in a plain-text format. The page uses a dark backdrop with a stylized SVG background image and prominently shows the dataset size, row count, and column count in a large, pink monospace block. It loads a CSV file from a GitHub Gist using D3 v7's `d3.csv()` method, calculates the file size in kilobytes with `d3.csvFormat().length`, and updates the HTML `pre` element's text content to display the results.