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“NaN” usually means **Not a Number**.
- **In programming (IEEE 754 floating-point):** it’s a special value representing an undefined/invalid numeric result, e.g.
- `0.0/0.0`
- `sqrt(-1)` (in real-number math)
- parsing a non-numeric string as a float
- **Behavior:**
- `NaN` is **not equal to anything**, even itself: `NaN == NaN` is `false`
- it tends to **propagate**: most operations with `NaN` produce `NaN`
- you check it with functions like `isnan()` / `Number.isNaN()` / `math.isnan()`
If you tell me the context (Python/JS/C++/dataframe/etc.), I can show exactly how to detect and handle it there.