ICE-6

ICE 6 Manasa V Jadda

This visualization displays earthquake magnitudes using a horizontal bar chart of the top 12 seismic events. The chart highlights each earthquake’s title on the y-axis and its magnitude on the x-axis, with red gridlines marking tick values. The code uses React with hooks and D3 v5’s `scaleBand`, `scaleLinear`, `csv` parsing, and SVG rendering to draw the bars. Data is loaded from a GitHub-hosted CSV file, with a basic color scheme and minimal styling.

MManasa891-git

85% match

ICE-6

This visualization displays the population growth rankings of Indian states in 2018 as a horizontal bar chart. It shows the top 20 states from a CSV dataset, with bar lengths representing the numeric ranking values on a linear scale. The React-based application loads data with `d3.csv`, slices the first 20 rows, and renders SVG rectangles using `d3.scaleBand` for the state categories and `d3.scaleLinear` for the ranking axis. Axis tick marks and labels are generated manually from the scales, with styling controlled by the accompanying CSS file.

RRamch16

84% match

ICE 6 Rendering Marks and Channels

This example shows a bar chart of the top 10 most populated states in India, using horizontal bars to encode population size. The chart loads data from a CSV file via `d3.csv` and renders with React and SVG. It uses `d3.scaleBand` for the y-axis state categories and `d3.scaleLinear` for the x-axis population values, with `d3.max` to determine the scale domain. Axes are drawn manually using SVG elements rather than d3 axis components, and gray grid lines are added for each tick value.

EEshwarreddyt

83% match

ICE-6 DV

This example displays a horizontal bar chart comparing the population of the first 20 U.S. states from a CSV dataset. Built with React and D3 v5, it uses `d3.csv` to load data, `scaleBand` for the y-axis categories, and `scaleLinear` for the x-axis values. The SVG rendering includes custom axis ticks and blue grid lines, with `rect` elements representing each state’s population.

ICE-6 DV

This example displays a horizontal bar chart of Indian state populations from a local CSV file, using SVG rendering with D3 v7. It shows population values per state, with each bar’s length encoding the data. The code employs `d3.csv`, `scaleLinear`, `scaleBand`, `axisLeft`, and `axisBottom` to construct the visualization. The bars are styled black via CSS, and the chart includes margins and axes, with the data loaded asynchronously and multiplied by 1000.

ICE-6

This horizontal bar chart visualizes the top 20 countries by population, with red bars extending from a shared baseline. The visualization uses React to manage state and D3 v5’s `scaleBand` for the categorical y-axis and `scaleLinear` for the numeric x-axis. Data is loaded asynchronously via `d3.csv` from a GitHub gist. Gridlines and tick labels are manually rendered as SVG elements using D3’s `ticks()` method, with the chart displayed within an SVG container on an HTML page.

Ssri7harsha

ICE-6 DV

A horizontal bar chart displays the top 10 most populous US states, ranking them by their 2019 population values. The visualization loads data from a CSV file using `d3.csv`, then scales the bars with `d3.scaleBand` and `d3.scaleLinear`. The chart is built with React components and rendered as SVG, with axis ticks and grid lines generated manually from the scales. The interface includes a title and a loading state while data is being fetched.

ICE-6 Dv

This bar chart displays the top 10 U.S. states by population from the year 2000, using data loaded from a CSV file via `d3.csv`. The visualization, built with React hooks and D3, renders an SVG bar chart where each state’s population is positioned using `scaleBand` and `scaleLinear`, with axes labels and red gridlines generated from scale ticks.