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fromRealpython
3 days ago
Python

Episode #296: Managing Polars Schema Issues & Profiling GitHub Users - The Real Python Podcast

fromRealpython
3 days ago
Python

Episode #296: Managing Polars Schema Issues & Profiling GitHub Users - The Real Python Podcast

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Python
fromMicrosoft for Python Developers Blog
3 weeks ago

Introducing Apache Arrow Support in mssql-python - Microsoft for Python Developers Blog

mssql-python now fetches SQL Server data directly as Apache Arrow structures, improving speed and memory efficiency for data handling in various libraries.
Data science
fromInfoQ
5 months ago

Decathlon Switches to Polars to Optimize Data Pipelines and Infrastructure Costs

Migrating small-to-medium data workloads from Apache Spark to Polars yields major performance and cost improvements by enabling single-node execution and faster in-memory processing.
fromPycoders
5 months ago

PyCoder's Weekly | Issue #712

Exploring Quantum Computing & Python Frameworks What are the recent advances in the field of quantum computing and high-performance computing? And what Python tools can you use to develop programs that run on quantum computers? This week on the show, Real Python author Negar Vahid discusses her tutorial, "Quantum Computing Basics With Qiskit." REAL PYTHON podcast
Python
#pandas
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Python
fromInfoWorld
7 months ago

7 newer data science tools you should be using with Python

Several lesser-known Python data-wrangling tools, including ConnectorX and DuckDB, enable faster, parallelized database loading and in-process OLAP analytics beyond Pandas/Numpy.
Startup companies
fromTechCrunch
7 months ago

The startup behind open source tool Polars raises $21M from Accel | TechCrunch

Polars raised €18 million to scale its Rust-based high-performance data processing platform, funding Polars Distributed and Polars Cloud for petabyte-scale workloads.
fromHackernoon
3 years ago

Pandas vs Polars in 2025: Choosing the Best Python Tool for Big Data | HackerNoon

Pandas is a Python library used for data analysis and manipulation on labeled datasets. The core mission of the Pandas development team is to be the fundamental high-level building block for practical, real-world data analysis in Python. It provides tools and methods for aligning, merging, transforming, and managing data from various persistent stores, positioning itself as the definitive tool for data analysis in Python.
Python
Data science
fromTalkpython
11 months ago

10 Polars Tools and Techniques To Level Up Your Data Science

Polars offers numerous advantages over Pandas, especially when enhanced with tailored libraries.
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