ICE_7_Yaswanth_Duddu

Yaswanth_duddu_ICE7

This reusable scatter plot shows the relationship between hours studied and exam scores for 50 students, with attendance percentage encoded as color and assignment completion as point radius. The visualization is built with D3 v7, using a queryable ScatterPlot function that accepts custom accessors for x, y, radius, and color. The code implements scales for positioning and sizing, axis generators for the plot frame, and SVG circle elements with tooltips via the append('title') API. The dataset is loaded from a CSV file containing student records with eight variables.

93% match

ICE_7_Yaswanth_Duddu

A reusable D3 v7 scatter plot displays study habits across 30 students, mapping hours studied to exam scores. Each SVG circle encodes attendance through a purple-blue color scale and assignment completion via radius size. The chart includes gridlines, axes, and interactive hover tooltips showing all four data dimensions. A custom ScatterPlot component function applies margin conventions and D3 scales, with the gradient legend indicating three attendance categories.

92% match

ICE_7_Yaswanth_Duddu

This scatter plot shows the relationship between study hours and math scores for ten students, with each circle representing an individual student’s data point. The visualization uses D3.js v6 to load data from a CSV file, scales the x and y axes linearly, and renders circles in an SVG container. The code converts the CSV strings to numbers, creates x and y scales, appends axes, and positions the steel-blue circles using the scale functions to map study hours and scores to pixel coordinates.

92% match

Ice7 scatter plot

This scatter plot visualizes exam scores against study hours for 15 students, revealing a clear positive correlation between the two variables. Each point is labeled with its student number, and the axes include descriptive titles. The visualization uses D3 v7 to load CSV data with `d3.csv`, scales the data with `d3.scaleLinear`, and renders axes with `d3.axisBottom` and `d3.axisLeft`. The reusable `createScatterPlot` function generates an SVG with customizable colors and labels.

88% match

ICE 7 Reusable scatter plot

This reusable scatter plot shows the relationship between study hours and exam scores, with each point representing a student’s performance. The D3.js component implements chainable accessors for configurable dimensions, margins, labels, and title, using `d3.scaleLinear`, `d3.extent`, `d3.axisBottom`, and `d3.axisLeft` to generate SVG axes. Data is loaded from a CSV file and rendered as green circles, demonstrating a modular approach to building interactive charts with d3.v7.

87% match

Ice 7 Scatter plot harshitha dontha

This reusable scatter plot shows the relationship between study hours and exam scores, with each point representing a student. The chart uses d3.scaleLinear for both axes and renders circles via SVG. The code demonstrates a modular chart function pattern, loading data from a CSV file and displaying axes with d3.axisBottom and d3.axisLeft. The visualization also includes a separate implementation that supports custom symbol shapes and color encoding through d3.symbol and d3.scaleOrdinal.

86% match

Yaswanth_duddu_ICE7

The visualization explores the relationship between student study hours, attendance, assignments, and exam scores using a scatter plot. Each point represents a student, with positions derived from the CSV data and visual encoding mapping study metrics. Rendered using HTML5 Canvas with CSS styling, the plot demonstrates that increased study hours and attendance generally correlate with higher exam performance. A 12em bold message overlays the chart, suggesting a focused narrative element. This example uses Canvas drawing methods and encoded CSV parsing to illustrate academic achievement patterns.

86% match

Ice 6 Scatter_data

This scatter plot visualizes the relationship between study hours and exam scores, with each point representing a student. The chart reveals a curved pattern where scores initially rise with study hours, peak around 48 hours, then decline, suggesting diminishing returns. Built with D3 v7, the visualization loads data from a CSV file and renders circles as SVG elements. The code uses `d3.csv` to parse the data, `d3.scaleLinear` for both axes, and `d3.axisBottom` and `d3.axisLeft` to generate the scales.