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- Import from Numpy 11228
- It is possible to query Numpy arrays from DuckDB. There is no need to register the arrays manually – DuckDB can find them in the Python process by name thanks to replacement scans . For example: import duckdb import numpy as np columns = {
...").fetchall()) [(1, 9.0), (2, 8.0), (3, 7.0)] Each array supplies one column. DuckDB also accepts a two-dimensional array, treating each outer array as a column. Transpose an array whose outer dimension represents rows before querying it. A masked array... - https://man.mtool.work/duckdb/2.0/guides/python/import_numpy.html
- Struct Data Type 7485
- Conceptually, a STRUCT column contains an ordered list of columns called “entries”. The entries are referenced by name using strings. This document refers to those entry names as keys. Each row in the STRUCT column must have the same keys.
...as larger than any non- NULL value. Specifically: If every entry of s1 is not distinct from the corresponding entry of s2 (treating two NULL s as equal), then s1 and s2 compare equal. else, for the first index i where s1.value[i] is distinct from s2.valu... - https://man.mtool.work/duckdb/2.0/sql/data_types/struct.html
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