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docs: drop the DataFrame API from the SQL manual
DataFrame support is not going ahead, so the pages documenting it come out: the relational operations and the expression system, both of which described only that API. The manual was framed around having two query surfaces and choosing between them. With one, that framing is gone — the overview now leads with SQL over Arrow Flight SQL and what the dialect is, rather than with a comparison to something that will not exist. The function reference keeps everything that was about SQL: the DataFusion version, how Lance columns map onto its type system, the pseudo-columns, blob handling, and `fts()`. Only the section on reaching functions through the Python wrapper is replaced, since the wrapper is going too. Mentions of pandas and polars DataFrames elsewhere in the documentation are unrelated and untouched.
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@@ -115,19 +115,9 @@ A pseudo-column produced by `fts()`, carrying relevance for the row. It behaves
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like a normal column — order by it, filter on it, project it — and exists only
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in a relation that came from `fts()`.
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## From the DataFrame API {#from-dataframe}
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## Reaching a function LanceDB does not name {#escape-hatch}
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The [DataFrame API](/sql/dataframe) wraps five aggregates as Python functions —
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`sum`, `avg`, `min`, `max`, `count`. Everything else in the DataFusion reference
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is reachable through `func(name, *args)`:
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```python
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from lancedb import col, func
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df.select(func("date_trunc", "month", col("created_at")))
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df.filter(func("regexp_like", col("title"), "^intro"))
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```
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`func()` is not checked when you build the plan — an unknown name or a wrong
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argument count surfaces when the query runs on the server. That is the trade for
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reaching the whole function set without a wrapper per function.
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Nothing here wraps or restricts the DataFusion set — a query reaches any
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function in the reference above by writing it. If a name is not recognised,
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check it against the reference for the version this page pins rather than
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assuming it is unsupported.
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