Anaconda, Inc.

🚀 Anaconda, Inc. has launched the public beta of Anaconda Code, now available within the Anaconda Toolbox for Excel! This add-in empowers users to write and run Python code locally within Excel, offering flexibility, control, and enhanced data analysis capabilities. 🐍📊 Since launching Python in Excel with Microsoft 365 last year, the number one request from the community has been to let them run Python code locally on their workbooks. Excel users have always valued security, shareability, and reproducibility in their spreadsheets and we're proud to deliever that with Anaconda Code. Users can access Anaconda Code via the Anaconda Toolbox, an add-in for Microsoft Excel that equips users with our powerful AI assistant designed specifically for data science tasks while making it easy to collaborate with your co-workers. With the combination of Anaconda Code and Anaconda Toolbox, Excel users can now: 🐍 Use the Anaconda Assistant, our AI-chat companion for learning and coding Python ✍️ Write, save, and share Python code snippets for enhanced productivity. 📊 Create powerful visualizations using accessible templates and libraries. 🛝 Efficiently access data, conduct analysis, and share your work with otheres This release is a direct result of our commitment to users and the broader Python community. We're excited to further democratize Python and bring the innovation of open-source software to Microsoft Excel users! Many thanks to the incredible team behind this including Tiffany McEachern, Timothy Hewitt, Chris Styduhar, Albert DeFusco, Jim Kitchen, Cheng H. Lee, Rachel Jordan, and so many more! Learn more in our press release! 👉 https://lnkd.in/gTmqJTfm

Did you know you can now run Python directly in Excel locally with the new Anaconda Code add-in? 📊 + 🐍 = 💚 Since Python in Excel was introduced, users have asked for the ability to run Python locally. We listened! The public beta of Anaconda Code is now live, allowing users to run Python code locally in Excel. 🌟 Why Anaconda Code? ⚡️ Cells Run Independently: Faster performance by running cells only when modified. 🤝 Flexible Data Handling: Choose between pandas dataframes, NumPy arrays, or lists. ✍️ Editable Initialization: Customize imports and definitions to fit your needs. 🛠️ Customizable Environment: Select and pin packages from PyPI for seamless sharing. Users can start using Anaconda Code today by visiting AppSource, Microsoft 365’s add-in marketplace, and downloading the Anaconda Toolbox.  Read more in our blog post and follow Anaconda, Inc. for more Python in Excel updates! 🔗 https://lnkd.in/gUBzpAES

Yes! Jess Haberman ...O'Reilly-alumni, now with Anaconda, Inc. will be co-presenting the session on the future of data education at the upcoming Data Day Texas. Details to follow. https://lnkd.in/eZxQn9yA Seriously, this is the year not to miss. Join us in Austin!

Over the past decade, open-source software has revolutionized data science and AI development. With transparency, cost-effectiveness, and continuous innovation driven by a vast community, open-source adoption is skyrocketing across industries. To harness the power of open source, organizations must prioritize: 🔒 Security: Ensuring packages are free from vulnerabilities. 🚀 Scalability: Seamlessly accommodating growth. 🛠️ Integration: Interoperating with existing tools and workflows. ✅ Dependency Management: Simplifying access and compatibility. 🤝 Community Commitment: Leveraging global expertise and innovation. Read more from Anaconda, Inc.'s Rob Futrick in Forbes here 🔗 https://lnkd.in/gKesmR33

Here's a fun post I worked on with Andrew H. analyzing past Olympic game data. Interesting to see how the Games have changed over time - like how historically it's the most equal its ever been. We used a combination of open-source tools like Panel and Bokeh, and Anaconda, Inc.'s cloud Notebooks to run code and visualize the data. You can read all about it here: https://lnkd.in/gmc_xKhf

The #Olympics aren’t just a showcase of athletic prowess; they’re a treasure trove of data waiting to be explored. Today marks the beginning of the Paris 2024 Olympics and here at Anaconda we thought what better way to get involved than to analyze past Olympic game data to show how the Games have evolved over time. In a blog post from Anaconda, Inc.’s Andrew H., we employed the open-source projects Panel and Bokeh using our free Anaconda Notebooks to visualize modern Olympic game data from 1896 to present day. The post uncovers: ⭐ The countries that hosted the most Olympic games 🏅 The countries and athletes that won the most Olympic medals ♂️♀️ Which Olympic games are exclusive to gender 📅 When each sport took place in the Olympics.. And more! Read our post and let us know what you took away from the data in the comments 💬 🔗 https://lnkd.in/gPfPKYM6

Check out this great website made using Anaconda, Inc. and PythonAnywhere! So proud to see our user community taking our tools and building incredible things. What kind of projects are you working on? 🤔

Excited to announce that you can now find NVIDIA CUDA Toolkit 12 on Anaconda, Inc.'s main (defaults) channel!! You can read all about it in my blog post on the Anaconda blog ⬇ https://lnkd.in/ec8fK7ZW

🚀 Exciting News! NVIDIA CUDA Toolkit 12 is now available on Anaconda, Inc.'s main (defaults) channel, upgrading from version 11.8. CUDA Toolkit provides a robust development environment for building high-performance, GPU-accelerated applications across platforms. Previously, Anaconda distributed runtime libraries; now, we also include compilation and development tools (nvcc, nvrtc, cccl, nsight). Components are individually packaged, saving you time and disk space. 🔑 Key features: ⭐️ Support for NVIDIA Ampere and Hopper architectures, as well as Arm ⭐️ Multi-OS drivers, runtime kernels, MIG, Tensor Cores, CUDA graphs, confidential computing, NVIDIA NVLink ⭐️ C++, Fortran compilers, OpenACC directives ⭐️ Libraries for scientific computing, data science, AI/ML, graphics With the CUDA Toolkit users can manage both Python and non-Python software in one environment with Anaconda, streamlining your AI and data science initiatives. Learn more about the update in our blog linked in the comments! 🔗 Thanks to our fantastic team behind this including Tiffany McEachern, Albert DeFusco, Cheng H. Lee, Chris Styduhar, James Bednar, Rachel Jordan, Daniel Petry and so many more!!