Crunching Large Datasets Made Fast and Easy: the Polars Library
#datascience #bigdata #python #dataengineering #parallelcomputing #polarslibrary #polars #crunchinglargedatasets
https://hackernoon.com/crunching-large-datasets-made-fast-and-easy-the-polars-library
#datascience #bigdata #python #dataengineering #parallelcomputing #polarslibrary #polars #crunchinglargedatasets
https://hackernoon.com/crunching-large-datasets-made-fast-and-easy-the-polars-library
Hackernoon
Crunching Large Datasets Made Fast and Easy: the Polars Library | HackerNoon
Processing large data, e.g. for cleansing, aggregation or filtering is done blazingly fast with the Polars data frame library in python thanks to its design.
Exploring Data Operations with PySpark, Pandas, DuckDB, Polars, and DataFusion in a Python Notebook
#python #pandas #polars #datafusion #duckdb #dremio #dataquery #datawriting
https://hackernoon.com/exploring-data-operations-with-pyspark-pandas-duckdb-polars-and-datafusion-in-a-python-notebook
#python #pandas #polars #datafusion #duckdb #dremio #dataquery #datawriting
https://hackernoon.com/exploring-data-operations-with-pyspark-pandas-duckdb-polars-and-datafusion-in-a-python-notebook
Hackernoon
Exploring Data Operations with PySpark, Pandas, DuckDB, Polars, and DataFusion in a Python Notebook | HackerNoon
In this blog, we'll demonstrate how to perform basic data operations using PySpark, Pandas, DuckDB, Polars, and DataFusion.