memtable

xorq.api.memtable(data, *, columns=None, schema=None, name=None)

Construct an ibis table expression from in-memory data.

Parameters

Name	Type	Description	Default
data		A table-like object (pandas.DataFrame, pyarrow.Table, or polars.DataFrame), or any data accepted by the pandas.DataFrame constructor (e.g. a list of dicts). Note that ibis objects (e.g. MapValue) may not be passed in as part of data and will result in an error. Do not depend on the underlying storage type (e.g., pyarrow.Table), it’s subject to change across non-major releases.	required
columns	Iterable[str] | None	Optional of column names. If provided, must match the number of columns in data.	None
schema	SchemaLike | None	Optional Schema. The functions use data to infer a schema if not passed.	None
name	str | None	Optional name of the table.	None

Returns

Name	Type	Description
	Table	A table expression backed by in-memory data.

Examples

>>> import ibis
>>> t = ibis.memtable([{"a": 1}, {"a": 2}])
>>> t

>>> t = ibis.memtable([{"a": 1, "b": "foo"}, {"a": 2, "b": "baz"}])
>>> t

Create a table literal without column names embedded in the data and pass columns

>>> t = ibis.memtable([(1, "foo"), (2, "baz")], columns=["a", "b"])
>>> t

Create a table literal without column names embedded in the data. Ibis generates column names if none are provided.

>>> t = ibis.memtable([(1, "foo"), (2, "baz")])
>>> t