ENH: Fix lowess extrapolation #9221
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NumPy's guide.
Really, #7337 didn't have anything to do with extrapolation per se. In most of the examples, you just get to a perfect fit and we weren't stopping so it goes off the rails. See #9220.
In the last case, where frac=.3. Since that results in 3 data points in the neighborhood, and with a radius of 2 and them being spaced like 1, 2, 3, you're only ever going to get 2 non-zero weights. Really, you only need your weights to sum to something greater than zero to do the WLS step (for better or worse), so I made that change. That revealed the test case where we have so many ties. Instead of handling this through weights counting, I added a guard for radius of zero.
Draft because this also includes #9220 until/if merged.