Skip to main content
SimilarExport ZIP
100%

Fork of Fork of Bonus ICE Scatter plot using D3.js

✓ Published0🌍 Public
Vvryvarma5577@gmail.com
Last edited Apr 4, 2023
Created on Apr 4, 2023

This example shows two 3D scatter plots of agricultural data, comparing crop production and district names against crop year, season, and area. The visualization uses Plotly's `scatter3d` traces rendered inside a `myDiv` container, with data loaded from a CSV file via D3.js’s `d3.csv`. Each trace maps distinct dataset columns to the x, y, and z axes, using marker size, color, and opacity to differentiate the points. The code relies on Plotly’s `newPlot` API to render the interactive chart.

AI-generated description

A bare minimum HTML page demonstrating use of CSS and JavaScript.

See also React Starter.

MIT Licensed

Similar vizzes

Loading thumbnail…

Fork of Fork of Bonus ICE Scatter plot using D3.js

This example shows two 3D scatter plots of agricultural data, comparing crop production and district names against crop year, season, and area. The visualization uses Plotly's `scatter3d` traces rendered inside a `myDiv` container, with data loaded from a CSV file via D3.js’s `d3.csv`. Each trace maps distinct dataset columns to the x, y, and z axes, using marker size, color, and opacity to differentiate the points. The code relies on Plotly’s `newPlot` API to render the interactive chart.

Vvryvarma5577@gmail.com
100% match
Loading thumbnail…

Fork of Bonus ICE Scatter plot using D3.js

This example shows two interactive 3D scatter plots of Indian agricultural data, with one trace mapping crop, production, and district, and another mapping crop year, season, and area. It uses Plotly’s `scatter3d` type via `Plotly.newPlot` to render the markers, while D3.js (v3) loads the remote CSV data with `d3.csv` and processes rows using the `unpack` helper. The layout disables margins for a clean, full-window presentation.

Qqwxyyigesm
95% match
Loading thumbnail…

Fork of Bonus ICE Scatter plot using D3.js

This visualization displays agricultural data from a CSV file as two interactive 3D scatter plots. The first plot maps crop production across districts, while the second shows crop year, season, and area. Using Plotly’s JavaScript API (`Plotly.newPlot`), the code creates `scatter3d` traces with marker styling for size, opacity, and color. D3.js (`d3.csv`) fetches and parses the remote data, which is then transformed into trace objects via the `unpack` function. The chart renders inside a dedicated HTML `div`, demonstrating integration of D3 for data loading and Plotly for 3D visualization.

AAnitha Shivaramaiah
95% match
Loading thumbnail…

Fork of Fork of Bonus ICE Scatter plot using D3.js

This example creates a 3D scatter plot with two traces, each mapping different agricultural data columns from a CSV file. The first trace plots Crop, Production, and District_Name, while the second plots Crop_Year, Season, and Area. It uses D3.js to load the CSV data via `d3.csv` and Plotly.js to render the interactive `scatter3d` chart inside a `myDiv` element, with margins set to zero.

PPedram
94% match
Loading thumbnail…

Bonus ICE Scatter plot using D3.js

This example shows a 3D scatter plot of agricultural data, plotting two distinct traces that map crop production and area against district names and seasons. The visualization uses Plotly’s `scatter3d` type within a single `Plotly.newPlot` call, while D3.js loads the CSV dataset via `d3.csv`. The first trace uses crop, production, and district as x, y, and z coordinates, while the second uses crop year, season, and area, with markers styled by opacity, size, and color.

SShishiraRudrabhatla
90% match
Loading thumbnail…

Bonus ICE Scatter plot using D3.js

This example displays agricultural data from India as a 3D scatter plot, with each trace mapping different variables—crop, production, and district on the first trace, and crop year, season, and area on the second. It uses the Plotly.js library to render the `scatter3d` markers, loading CSV data through D3.js v3’s `d3.csv` method. The code defines two marker traces with distinct colors and opacity, then plots them in a single `myDiv` container with zero margins for a clean view.

Aav.dj.2000@gmail.com
89% match
Loading thumbnail…

3D Scatter plot using D3.js

This example presents an interactive 3D scatter plot built with Plotly.js and D3.js, visualizing agricultural crop data. It renders two marker traces from a CSV file: one mapping crop type, production, and district, the other correlating crop year, season, and area. The code uses `d3.csv` to load the dataset and `Plotly.newPlot` to draw the scatter3d traces within a DIV element. The visualization employs 3D markers with custom opacity and line styling to distinguish the two datasets, with the layout margins set to zero.

Ggayathrikavya
85% match
Loading thumbnail…

Fork of Bonus ICE Scatter plot using D3.js

This 3D scatter plot visualizes COVID-19 data across countries, showing two traces: one plotting cured cases against dead cases, and another plotting active cases against dead cases. The visualization uses Plotly’s `scatter3d` type within `Plotly.newPlot`, with D3.js handling CSV data loading via `d3.csv` and the `unpack` function to extract columns. Data originates from a GitHub-hosted CSV file containing per-country case counts, rendered as colored markers with configurable opacity and line styling in a minimal HTML page.

Pprathyusha-reddy-arch
82% match