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- Import from Numpy 11905
- 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 = {
...ray, treating each outer array as a column. Transpose an array whose outer dimension represents rows before querying it. A masked array is read with its mask: masked elements become NULL . my_masked_arr = np.ma.masked_array([1.0, 2.0, 3.0], mask=[False..., True, False]) duckdb.sql("SELECT * FROM my_masked_arr") ┌─────────┐ │ column0 │ │ double │ ├─────────┤ │ 1.0 │ │ NULL │ │ 3.0 │ └─────────┘ See Also DuckDB also supports ex... - https://man.mtool.work/duckdb/2.0/guides/python/import_numpy.html
- Data Ingestion 8222
- 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
...DataFrames, LazyFrames and Series, NumPy arrays, a dict of one-dimensional NumPy arrays, relations and Arrow objects. The masked elements in a NumPy masked array are NULL . In a dict of arrays, names that differ only in case get a suffix, so the keys... - https://man.mtool.work/duckdb/2.0/clients/python/data_ingestion.html
- Conversion between DuckDB and Python 7757
- 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
...es the data as a dictionary of NumPy arrays. A column without NULL values is a plain array. A column with NULL values is a masked array. Pandas df() fetches the data as a Pandas DataFrame fetchdf() and, on the connection, fetch_df() are older names of... - https://man.mtool.work/duckdb/2.0/clients/python/conversion.html
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