Document that NaN in a data variable is read as SQL NULL
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还没有人认领这个 Issue。
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- 1/5
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- 1-3 小时
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- 85/100
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- 描述清楚
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- 活跃
- 技术栈
- python
调研方向
首先检查 xarray_sql/df.py 中的转换以及 ADBC 方言，然后查看 docs/limitations.md 和读取文档，找到最适合添加此说明的位置。说明数据变量中的 NaN 会变成 SQL NULL，聚合函数会跳过它，并且无法将其读取为 NaN 值。
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描述
xarray-sql turns NaN in a data variable into SQL NULL when it scans a Dataset (pa.array(..., from_pandas=True) in xarray_sql/df.py, and the same in the ADBC dialects). That is deliberate, so aggregates skip missing values the way xarray's skipna does. I couldn't find it in the user docs, though, and it surprised me.
What I expected
That a float NaN stays NaN, as it does in a Parquet file or an Arrow table registered directly, and that SUM over a column with a NaN returns NaN.
What happens
import numpy as np, xarray as xr, xarray_sql as xql
ds = xr.Dataset({"x": (("t",), [1.0, np.nan, 2.0])}, coords={"t": [0, 1, 2]})
ctx = xql.Context()
ctx.from_dataset("v", ds)
ctx.sql("SELECT SUM(x) AS s, COUNT(x) AS n, COUNT(*) AS rows FROM v").to_pandas()
# s = 3.0, n = 2, rows = 3
isnan(x) on that row is NULL, not true, and DuckDB through xql.register behaves the same.
Where it mattered
A check that attention masks pairs out rather than weighting them by zero put a NaN in V and expected it to reach only the queries allowed to see it. Every output stayed finite, because the NaN had become a NULL that SUM skipped. The check uses +inf instead, which xarray-sql keeps as a value.
Suggestion
Document it, for example in docs/limitations.md or the reading docs: NaN in a data variable is read as NULL; aggregates skip it; there's no way to read a NaN as a value. Whether to offer an option to keep NaN is a separate question.
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