feat(operator): cut a numeric column into bins - #8481

The same gap as the timestamp parts, on the other kind of column. Grouping by a
continuous number puts almost every row in a group of its own, so counts per age
bracket or per price band could not be asked for; a user wanting them had to
write a Python UDF.

Two cuts, because they answer different questions. Equal width divides the span
into bins of one size; equal frequency cuts at the quantiles, so the bins hold
about as many rows as each other. The second is why the operator reads the whole
table before it emits: a quantile is not known until the last row has arrived.

The bin reads as its own range, "(2.5, 5.0]", which is a label to group by
rather than a number to do arithmetic on.

Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>

An equal-width cut has no edges to find when every cell of the column is
empty, and none when no row arrived at all, so pandas raises before the
suffix that keeps a hole a hole can run. Both renderings now skip the cut
in that case and let the suffix turn the holes into the empty bin labels
they already are.

The equal-frequency cut does not raise on the same table, but it goes
through the same guard: one shape of answer for a table with nothing in
it, whichever way it was asked to cut.

Two tests run the exported script over an all-empty column, an empty
table and a column with one hole, since the defect is what pandas does at
runtime rather than what the operator writes.

Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>

…-integration

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>

A nullable Float64 column read from Arrow can hold NaN as a value, which
notna() reports present, so an all-NaN column reached pd.cut and raised on
duplicate edges while the engine path left it uncut. The guard now tests a
float64 view. Adds a stored-NaN case to the runtime test.

Co-Authored-By: Claude Opus 5.5 <[email protected]>

Python's open() defaults to the locale's encoding, which is cp1252 on
Windows, while the spec writes these files as UTF-8.

Co-Authored-By: Claude Opus 5.5 <[email protected]>

pandas builds edges in float64, which cannot count by one past 2**53, so
an equal-width cut raised on duplicate edges and a quantile cut merged
the rows into one bin. An integer column is now cut as its distance from
the value nearest zero, and that value is added back to the labels.

Co-Authored-By: Claude Opus 5.5 <[email protected]>

…e same bin

Comparing category counts missed Int64 values near the limit, where the plain
cut keeps all bins but puts every row in one.

Co-Authored-By: Claude Opus 5.5 <[email protected]>

Co-Authored-By: Claude Opus 5.5 <[email protected]>