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Dynamic binning( Not yet complete)

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AArjun Rao
Last edited Nov 3, 2020
Created on Oct 30, 2020

This interactive visualization explores customer churn data from Kaggle, focusing on the relationship between estimated salary and credit score. Users can brush a salary range on a small bar chart to filter the main scatter plot, and use menus to select a specific country and gender for comparison. The display dynamically re-bins the salary axis into five bins based on the brush selection, with opacity highlighting the relevant data points. Built with the vega-lite-api and D3, it combines multiple selection types—interval brushing, dropdown menus, and radio buttons—to create a linked-view analysis tool.

AI-generated description

A visualization constructed using the vega-lite-api.

The data shown here comes from the Kaggle, via Gist.

I took help from https://observablehq.com/@uwdata/interaction?collection=@uwdata/visualization-curriculum.

You can select a range of salaries on the top graph to view that in the below graph. I have binned the salaries into 50 bins.

Additionaly, you can select which gender you want to focus on and the country the customers are from.

MIT Licensed

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