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An overview of the Sparse Array Ecosystem for Python

This article was originally published on the Quansight Labs Blog by Hameer Abbasi

Jul 4

This mind map illustrates the Sparse Ecosystem, branching into three main categories: Data structures, Algorithms, and Libraries. Data structures are divided into Common and Advanced types. Algorithms include Hard-coded operations for element-wise and matrix multiplication. Libraries showcased are scipy.sparse, cupyx.sparse, torch.sparse, and a generic sparse library. The map uses icons and color-coding to organize different aspects of sparse matrix computation and storage.

Jul 4

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Community-First Open Source: An Action Plan!

Quansight CTO Dharhas Pothina is here to discuss an action plan for achieving community-driven open source.

Jun 25

Community-First Open Source: An Action Plan!

Jun 25

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How Narwhals and scikit-lego came together to achieve dataframe-agnosticism

This article was originally published on the Quansight Labs Blog by Marco Gorelli.

Jun 18

How Narwhals and scikit-lego came together to achieve dataframe-agnosticism

Jun 18

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Taming the Toxic Python Environment on your Laptop

Local Reproducible Open Source Environments with conda-store

Jun 10

Taming the Toxic Python Environment on your Laptop

Jun 10

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PyTorch Progress as a General-Purpose Array-Oriented Computational Backend

This post was created from Travis Oliphant’s keynote at PyTorch Conference 2023 and originally posted on the Quansight blog. The full…

Jun 3

PyTorch Progress as a General-Purpose Array-Oriented Computational Backend

Jun 3

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Dataframe interoperability — what has been achieved, and what comes next?

This article was originally published on the Quansight Labs blog by Marco Gorelli.

May 30

An illustration showing a panda, a polar bear, and a narwhal relaxing together in an office setting. The panda is sitting at a desk with a laptop and potted plant, while the polar bear and narwhal are lounging in chairs. The image seems to symbolize different data manipulation libraries like pandas, Polars, and Narwhals coexisting and working harmoniously.

May 30

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Writing fast string ufuncs for NumPy 2.0

This article was originally published on the Quansight Labs blog by Lysandros Nikolaou.

May 29

May 29

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Gaining Traction: The Consortium for Python Data API Standards Releases Its 2023 API Specification

The revision of the array API standard is now ready for adoption by conforming array libraries.

May 13

Gaining Traction: The Consortium for Python Data API Standards Releases Its 2023 API Specification

May 13

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Staff Interview: 🌳Nebari: An Infrastructure Engineering Perspective

Hear from Quansight’s Senior Infrastructure Engineer, Chuck McAndrew, on how Nebari has transformed the landscape for deploying data…

May 6

Staff Interview: 🌳Nebari: An Infrastructure Engineering Perspective

May 6

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Nebari: The End-User Perspective

Hear from Quansight’s Kim Pevey on empowering data science teams with collaboration and efficiency.

Apr 26

Nebari: The End-User Perspective

Apr 26

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Quansight

We solve complex, data-related problems by leveraging the open source software at the foundation of innovation in machine learning and artificial intelligence.

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