![]() It comes with Conda, a package and environment manager that will make your work a thousand times better.Anaconda comes with a bunch of data science packages you’ll be all set to start working with data. You will be needing a lot of data science packages as you progress.You may already have Python installed on your computer, but as a data specialist, it will be beneficial to use Anaconda because: Installing Python packages and creating a virtual environment is simple with Anaconda, thus you can work on multiple projects conveniently. You can easily install, upgrade, or uninstall Python packages and environments. AnacondaĪnaconda is a distribution of libraries and software specifically built for data scientists and engineers. If you are working with data though, Anaconda is the way to go. ![]() To solve this problem we use virtual environments managed with libraries such as Virtualenv.Ī virtual environment lets you separate libraries required by different projects, so you can avoid conflicts. What’s the solution? Virtual environments In my experience and in many other people’s, it is really difficult to get these versions to play nicely together on one computer. While recent projects and libraries were in Python 3, a significant number of legacy projects and libraries were written in Python 2.Īs a data engineer, a lot of times you will be working with projects that require different library versions or different versions of Python. There are several versions of Python, majorly Python 2 or 3. In this tutorial, you will learn how to install Anaconda on Windows, macOS and Linux and why it is best rather than just installing only Python.
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