Results of 1 - 7 of about 7 for dtype (0.004 sec.)
- Integration with PyTorch 11996
- PyTorch tensors can be built from DuckDB query results by exporting each result batch as Apache Arrow . This pattern is useful when training or serving models on Parquet data because DuckDB can filter and project the input before the batche
...batch in reader: features = torch.tensor( np.column_stack( [ batch.column(0).to_numpy(), batch.column(1).to_numpy(), ] ), dtype=torch.float32, ) labels = torch.tensor(batch.column(2).to_numpy(), dtype=torch.int64) print(features.shape, labels) torch.... - https://man.mtool.work/duckdb/2.0/guides/python/pytorch.html
- Export to Numpy 10451
- The result of a query can be converted to Numpy arrays using the fetchnumpy() function, which returns a dictionary that maps each column name to a Numpy array. For example: import duckdb import numpy as np my_arr = duckdb.sql("SELECT unnest
...([1, 2, 3]) AS x, 5.0 AS y").fetchnumpy() my_arr {'x': array([1, 2, 3], dtype=int32), 'y': array([5., 5., 5.])} Then, the array can be processed using Numpy functions, e.g.: np.sum(my_arr['x']) np.int... - https://man.mtool.work/duckdb/2.0/guides/python/export_numpy.html
- Types API 10142
- The DuckDBPyType class, duckdb.sqltypes.DuckDBPyType , represents one of the data types . Use DuckDBPyType to describe SQL types when declaring function parameters, return types or casts. Python types such as int are accepted too: int descr
...int BIGINT str VARCHAR NumPy Scalar Types The table below shows the mapping of NumPy scalar types to DuckDB type. A NumPy dtype object does not convert: DuckDBPyType(numpy.dtype("int32")) raises a NotImplementedException . Type DuckDB type numpy.bool...t() con.execute("CREATE TYPE mood AS ENUM ('sad', 'ok', 'happy')") print(con.type("mood")) ENUM('sad', 'ok', 'happy') Nested Types list[child_type] list type objects map to a LIST type of the child type, which can itself be nested. import duckdb.sqlty...Union[type_1, ... type_n] typing.Union objects, and unions written as type_1 | type_2 , map to a UNION type of the provided types. import duckdb.sqltypes from typing import Union print(duckdb.sqltypes.DuckDBPyType(Union[int, str, bool, bytearray])) p... - https://man.mtool.work/duckdb/2.0/clients/python/types.html
- Data Ingestion 9215
- This page contains examples for data ingestion to Python using DuckDB. First, import the DuckDB package: import duckdb Then, proceed with any of the following sections. CSV Files CSV files can be read using the read_csv function, called eit
...read_csv("example.csv", header = False, sep = ",") Override types of the first two columns: duckdb.read_csv("example.csv", dtype = ["int", "varchar"]) Directly read a CSV file from within SQL: duckdb.sql("SELECT * FROM 'example.csv'") Call read_csv fr..._arrow(obj).fetchall()) [(6,)] [(1,), (2,), (3,)] Pandas DataFrames – object Columns pandas.DataFrame columns of an object dtype require some special care, since this stores values of arbitrary type. To convert these columns to DuckDB, we first go thr... - https://man.mtool.work/duckdb/2.0/clients/python/data_ingestion.html
- Conversion between DuckDB and Python 8288
- This page documents the rules for converting DuckDB results to Python and Python objects to DuckDB . Result Conversion: DuckDB Results to Python A result is read from a relation or, when using the DB-API / con.execute() , from the connectio
...execute("SELECT * FROM items").fetchnumpy() print(arr) {'item': array(['jeans', 'hammer', 'laptop', 'chainsaw', 'iphone'], dtype=object), 'value': array([ 20. , 42.2, 2000. , 500. , 300. ]), 'count': array([ 1, 2, 1, 10, 2], dtype=int32)} Fetch as an...5, "test"]]).fetchall()) [(['12345', 'test'],)] A NaN stays NaN inside a list, a struct, a map or a duckdb.Value of a nested type. A list that mixes datetime values with and without tzinfo becomes a TIMESTAMPTZ list as a query parameter and in values(... - https://man.mtool.work/duckdb/2.0/clients/python/conversion.html
- Python Client API 6743
- Connection class duckdb. Appender Bases: object append_row ( self , * args ) → None Buffer one row, one value per column, each converted as an executemany parameter would be append_rows ( self , rows : object ) → None Buffer each row of an
...Fetch a result as DataFrame following execute() disable_profiling ( self ) → None Disable profiling for subsequent queries dtype ( self , type_str : str ) → _duckdb._sqltypes.DuckDBPyType Create a type object by parsing the ‘type_str' string duplicate...e a relation object for the named view. class duckdb. Statement Bases: object property expected_result_type Get the expected type of result produced by this statement, actual type may vary depending on the statement. property named_parameters Get the...page . drop ( * columns : str ) → DuckDBPyRelation Remove columns. Detailed examples can be found at Relational API page . dtypes Return a list containing the types of the columns of the relation. Detailed examples can be found at Relational API page... - https://man.mtool.work/duckdb/2.0/clients/python/reference/
- Relational API 6743
- The Relational API builds a query one step at a time from Python. A relation, a DuckDBPyRelation , is a piece of SQL text: the methods of the Transformation and Functions sections return a new relation whose text extends the one they were c
...InvalidInputException . Most are the option of the same name of the SQL read_csv function ; sep and delimiter are delim , dtype is dtypes , na_values is nullstr , skiprows is skip , quotechar is quote , escapechar is escape , date_format is dateforma...cannot be combined with delimiter . Detected when omitted. * delimiter : str, keyword-only, default: None Same as sep . * dtype : dict[str, str], list[str], keyword-only, default: None Column types, as a dict of column name to type or a list of types...ewline character itself, such as '\n' , is refused. * columns : dict[str, str], keyword-only, default: None Column names and types, as a dict of column name to type name; the types are then not detected. * auto_type_candidates : list[str], keyword-onl... - https://man.mtool.work/duckdb/2.0/clients/python/relational_api.html
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