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Add TSGap package introduction and tutorial - #998

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Summary

This post introduces TSGap, a recently accepted pyOpenSci package for
simulating reproducible missingness in time-series imputation benchmarks.

It covers:

  • missingness mechanisms and temporal patterns;
  • interpretation of structured MAR/MNAR masks;
  • a runnable block-missingness example;
  • missing-rate and evaluation semantics; and
  • links to the documentation, source, and PyPI package.

The post includes an existing TSGap visualization as its header image.

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