Pothuguntla Pranitha

TAsk 9 & 10 - Area Chart

Task 9 and 10 - PieChart

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Reusable Scatter plot Task 9 & 10

Using the Iris dataset, this visualization presents an animated scatter plot where the x-axis cycles through sepal and petal measurements. Iris species are distinguished by colored points (skyblue, lightgreen, orange), with labels for margin, axis, and legend rendered via D3 selection methods. Built with reusable D3 module patterns, the plot updates its axis scales and positions every few seconds using `setInterval` and D3's `scaleLinear`, `axisBottom`, and `axisLeft` APIs. The SVG graphics and smooth axis transitions demonstrate a dynamic, parameter-driven scatter plot example.

Crop_Yield Data

This example visualizes year-wise crop production across Indian states using a scatter plot. Each circle represents a data point, with the x-axis showing the crop year, the y-axis showing production quantity, and color encoding the state using a category20 color scheme. Hovering reveals the crop name via a tooltip. The code leverages the Vega-Lite API, registering both Vega and Vega-Lite with a custom tooltip handler, and loads data from a remote CSV file using d3.csv. The visualization auto-fits its dimensions to the window size.

ICRISAT District Level Data - Rice Production BarChart

Crop_Yield Data Viz

Crop_Yield - Stacked Bar Chart

Crop_Yield Pie Chart

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crop_yield

This bar chart shows total rice production for each state in India, using data from the ICRISAT District Level dataset. The visualization aggregates district-level production figures by state, displaying the sums as color-coded bars that reveal regional yield differences. Built with D3 v7, the chart uses `d3.rollup` for aggregation, `d3.scaleBand` and `d3.scaleLinear` for axes, and a `d3.scaleOrdinal` color scheme. Interactive tooltips display each state’s total production on hover, rendered as an HTML overlay with opacity transitions.

Project_Crop_Yield

Project_crop_yield

Project_crop_yield

Activity6_Task2_Q2

Activity6_Task3_Q3

This scatter plot visualizes the relationship between Quantity and Profit from the Superstore dataset, with each point’s shape and color encoding the order priority (Critical, High, Medium, or Low). The visualization uses D3.js (v6) to load the CSV data, apply linear scales for the axes, and render SVG paths with symbols like circles, squares, diamonds, and triangles. Axis labels and ticks are styled explicitly, while the plot fills the browser window. The code leverages `d3.csv`, `scaleLinear`, `axisLeft`, `axisBottom`, and `d3.symbol` for custom point shapes.

Activity6_population_Q1.1

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Activity6_Task4_Q4.

Activity6_Task4_Q4

Activity6_Task3_Q3

Activity6_Task2_Q2.1

Activity6_Task4

This bubble chart shows the correlation between average horsepower, torque, and highway MPG across 31 car makes. Each circle’s position encodes horsepower and torque, while its radius represents highway MPG, and color distinguishes manufacturers. Hovering reveals the car make via a tooltip. The visualization uses d3.csv to load data, d3.scaleLinear for axes and sizing, d3.scaleOrdinal with interpolateTurbo for coloring, and SVG circles with mouse event handlers for interaction. A legend displays MPG values and make colors.

Activity6_Task3_3.1

Activity6_Task3

Activity6_Task3_3.2

Activity6_population_Q1.2

Activity6_

Activity6_Task2

Activity6_Task2

activity 6_Task 1

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5 Buddhas - Polygon

The visualization shows five overlapping Buddha silhouettes, each rendered in a distinct color and arranged within an SVG canvas. Behind them, a field of randomly generated, semi-transparent polygons is drawn, each rotated 45 degrees and filled with RGB values computed from random calculations. Built with React and rendered through SVG, the code uses the `map` function to generate hundreds of polygon elements, while the Buddha shape itself is defined by a complex path data string, layered onto the chaotic geometric background.

5 Buddhas

Five Buddhas renders repeating layered Buddha silhouettes from SVG path data, overlaid with hundreds of translucent circles that use random positioning and color values. The React application maps over nested arrays to generate the circles, which are drawn in black with varying red, green, and blue components and an opacity of 0.8. The static Buddha paths are transformed and scaled within an SVG canvas, while the randomized circle distribution creates a colorful, overlapping visual effect across the composition.

5 Buddhas

Five Buddhas arranges layered, overlapping Buddha silhouettes in a five-fold composition against a black background. Each figure is constructed from SVG paths, surrounded by a dense field of randomly positioned, semi-transparent colored circles. The work uses React with ReactDOM to render the static vector graphics, while the accompanying JavaScript generates the scatter of circles with properties determined by the `Math.random()` function, producing a vivid, abstract halo of color around the central forms.

5 Buddhas

Five Buddhas presents a black-and-white line drawing rendered as an SVG path, mapped twenty times across the canvas to create a grid of overlapping, semi-transparent lotus silhouettes against a black background. Each Buddha is filled with a randomly generated RGB color, producing a variegated, kaleidoscopic effect as the repeated outlines layer on top of each other. Built with React and ReactDOM, the code generates an SVG element containing nested loops that map over an array to replicate the complex path data, with the fill color computed using `Math.random()` for each circle and path.