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Churn data based on multi filters

✓ Published2🌍 Public
AArjun Rao
Last edited Nov 3, 2020
Created on Oct 21, 2020

This visualization explores customer churn data from Kaggle, showing the relationship between estimated salary, credit score, and churn status through a bar chart and point plot. Users can brush a salary range on the top graph, which filters the scatter plot below, and use dropdown and radio menus to filter by geography and gender. Built with the vega-lite-api library, it uses `vl.selectInterval` for brushing, `vl.selectSingle` for menu-based filtering, and `vl.vconcat` to compose the linked views.

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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