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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 ...
Choose whether to add Anaconda to your PATH environment variable or register Anaconda as your default Python. We don’t recommend adding Anaconda to your PATH environment variable, since this can interfere with other software.
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Anaconda® Distribution is a free Python/R data science distribution that contains: conda - a package and environment manager for your command line interface. Anaconda Navigator - a desktop application built on conda, with options to launch other development applications from your managed environments.
The official Anaconda and Miniconda Docker images are on Docker Hub. If you have a CDH (Cloudera Distributed Hadoop) cluster, install the Anaconda parcel using Cloudera Manager. The Anaconda parcel provides a static installation of Anaconda, based on Python 2.7, that can be used with Python and PySpark jobs on the cluster. Troubleshooting
This guide to getting started with conda goes over the basics of starting up and using conda to create environments and install packages. Tip. Anaconda Navigator is a graphical desktop application that enables you to use conda without having to run commands at the command line.
Anaconda is a distribution of the Python and R programming languages for scientific computing (data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment.
Contents. Starting conda on Windows, macOS, or Linux. 2 MINUTES. Managing conda. Verify that Anaconda is installed and check that conda is updated to the current version. 3 MINUTES. Managing environments. Create environments and move easily between them. 5 MINUTES. Managing Python.
In this entry-level course, we’ll show you when and how to use Anaconda tools. You’ll learn about packages, conda environments, Jupyter Notebooks, integrated development environments (IDEs), and more. We’ll walk you through a Python program (in a notebook and in an IDE) and see what happens when a bug in Python code is identified.
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