![]() Conda even makes it easy to switch between Python 2 and 3 (you can learn more here). ![]() This is highly advantageous as you don't have to manage dependencies between multiple packages yourself. If you need additional packages after installing Anaconda, you can use Anaconda's package manager, conda, or pip to install those packages. This is advantageous as when you are working on a data science project, you will find that you need many different packages (numpy, scikit-learn, scipy, pandas to name a few), which an installation of Anaconda comes preinstalled with. Anaconda is a package manager, an environment manager, and Python distribution that contains a collection of many open source packages.
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