Using SQL with pandas empowers data scientists to leverage SQL’s powerful querying capabilities alongside the data manipulation functionalities of pandas.
However, traditional database systems often demand the management of a separate DBMS server, introducing additional complexity to the workflow.
With DuckDB, you can efficiently run SQL operations on pandas DataFrames without the need to manage a separate DBMS server.
In this comparison, aggregating data using DuckDB is nearly 6 times faster compared to aggregating with pandas.
2 thoughts on “Efficient SQL Operations with DuckDB on Pandas DataFrames”
Does this help with making Joins of multiple tables?
I don’t see why not: https://duckdb.org/docs/sql/query_syntax/from.html
Comments are closed.