Anaconda gives superpowers to people who change the world

Anaconda

Leading Open Data Science Platform
Powered by Python

Why You’ll Love Anaconda

Making it easy to install, intuitive to discover, quick to analyze, simple to collaborate, and accessible to all.

  • Committed to Open Source. Now and forever.

    We believe in the power of open source, and you’ll never again experience vendor lock-in. Our team is active and committed Python ecosystem contributors that inspire and innovate some of the most popular Python packages. Our Anaconda community is 1M+ strong worldwide and is doubling each year.

  • Tested and certified packages to cover your back.

    Anaconda makes it easy for you to install and maintain Python environments. Our development team tests to ensure compatibility of Python packages in Anaconda. We support and indemnify Anaconda to mitigate your risk in using open source and meet your regulatory compliance requirements.

  • Explore and visualize complex data easily.

    Use your experience and curiosity to explore and analyze your data. Choose from a rich set of interactive visualizations to bring your data to life and tell an insightful story. Discover new patterns and anomalies that empower your team to realize impactful value from your data.

  • All the analytics you ever wanted and more.

    Python is the fastest growing language for data science. Anaconda includes 330+ Python open source packages and now includes essential R packages. This powerful combination allows you to do everything you want from BI to advanced modeling on complex, Big Data.

Anaconda Superpowers

  • Anaconda

    Open Source modern analytics platform powered by Python

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  • Anaconda Pro

    Anaconda with support and indemnification

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  • Anaconda Workgroup

    High performance Anaconda with team collaboration

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  • Anaconda Enterprise

    High performance Anaconda for Big Data with team collaboration

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What’s New

  • Open Data Science: Bringing “Magic” to Modern Analytics

    In the past, our analytics tools were proprietary, product-oriented solutions. These were necessarily limited in flexibility and they locked customers into the slow innovation cycles and whims of vendors. These closed-source solutions forced a “one size fits all” approach to analytics with monolithic tools that did not offer easy customization for different needs.

    Open Data Science has changed that. It offers innovative software—free of proprietary restrictions and tailorable for all varieties of data science teams—created in the transparent collaboration that is driving today’s tech boom.

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  • Accelerate 2.2 Released!

    We're happy to announce the latest update to Accelerate with the release of version 2.2. This version of Accelerate adds compatibility with the recently released Numba 0.25, and also expands the Anaconda Platform in two new directions:

    • Data profiling
    • MKL-accelerated ufuncs

     I'll discuss each of these in detail below.

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  • Conda + Spark

    In my previous post, I described different scenarios for bootstrapping Python on a multi-node cluster. In a follow-up to that post, I was asked if the machinery in Knit would also work for Spark. Sure--of course! In fact, much of Knit's design comes from Spark's deploy codebase. Here, I am going to demonstrate how we can ship a Python environment, complete with desired dependencies, as part of a Spark job without installing Python on every node.

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  • High Performance Hadoop with Anaconda and Dask on Your Cluster

    Dask is a flexible open source parallel computation framework that lets you comfortably scale up and scale out your analytics. If you’re running into memory issues, storage limitations, or CPU boundaries on a single machine when using Pandas, NumPy, or other computations with Python, Dask can help you scale up on all of the cores on a single machine, or scale out on all of the cores and memory across your cluster.

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