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The Desktop Portal to Data Science. Anaconda Navigator is a graphical user interface (GUI) that enables you to work with packages and environments without needing to type conda commands in a terminal window.Find the packages you want, install them in an environment, run the packages, and update them - all inside Navigator. Anaconda Navigator.

Anaconda Wikipedia

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Anaconda, Inc. provides Anaconda and Miniconda Docker images. Read the official Docker documentation and specifically the information related to Docker images. Begin by browsing the available Anaconda images on our Docker profile. To obtain a fully working Anaconda image: In a terminal window, run this command to display a list of available images:

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Working with conda#. Installing Anaconda Distribution or Miniconda gives you access to conda, Python, and thousands of other popular packages. Anaconda Distribution installs more than 250 of these packages automatically, while Miniconda is a more lightweight distribution that contains only conda, python, their dependencies, and a small number of other packages.

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The 2022.05 release of Anaconda Distribution features native compiling for Apple M1's ARM64 architecture (boasting 20% faster compute), Anaconda Navigator 2.1.4, conda 4.12.0, as well as several new and updated packages. 2022.05 is also the last release that will support win32. Link to the latest…

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Download Anaconda Distribution Version | Release Date:Download For: High-Performance Distribution Easily install 1,000+ data science packages Package Management Manage packages.

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Open an Anaconda Prompt (terminal on Linux or macOS) and follow these instructions. Installing a conda package# Enter the command: conda install package-name. Installing specific versions of conda packages# Include the desired version number or its prefix after the package name:

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The most basic way to create a new environment is with the following command: conda create -n . To add packages while creating an environment, specify them after the environment name: conda create -n myenvironment python numpy pandas. For more information on working with environments, see Managing environments.