Dynamic binning( Not yet complete)
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 descriptionA 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.
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