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I'll update the interpolation tester to use your provided dataset. This data appears to show some kind of declining metric (possibly volatility or probability) over a range from about 20,750 to 45,000, with values between 0.18 and 0.95.

Perfect! I've updated the interpolation tester to use your dataset. This data shows an interesting pattern - it starts high around 0.95 at x=20750, generally decreases to a minimum around 0.18 near x=39000, then slightly increases toward the end reaching about 0.29 at x=45000.

This dataset will be excellent for testing different interpolation methods because:

1. Linear interpolation will show the basic trend
2. Cubic spline will provide smooth curves through all points
3. Monotonic spline might struggle since the data isn't strictly monotonic (it has some local increases)
4. Polynomial methods (quadratic, cubic, quartic) will try to fit the overall trend
5. Log-normal interpolation could be interesting if this represents some kind of probability or volatility data

You can now test different interpolation methods on this real-world dataset and see how they handle the complex curve with both declining and slightly increasing sections.