If you get a command not recognized error like in the left side of the image below, proceed to step 3. This is checking if you already have Anaconda added to your path. Enter the commands below into your Command Prompt. Check if you already have Anaconda added to your path. The advantage of this is that you will be able to use Anaconda in your Command Prompt, Git Bash, cmder etc.Ģ. This is for the case where you didn't check the box in step 6 and now want to add Anaconda to your Path. You can install Microsoft VSCode if you wish, but it is optional.ĩ. If you want to be able to use Anaconda in your command prompt (or git bash, cmder, powershell etc), please use the alternative approach and check the box. This means you will have to use Anaconda Navigator or the Anaconda Command Prompt (located in the Start Menu under 'Anaconda') when you wish to use Anaconda (you can always add Anaconda to your PATH later if you don't check the box). The recommended approach is to not check the box to add Anaconda to your path. This is an important part of the installation process. Note your installation location and then click Next.Ħ. Read the license agreement and click on I Agree.ĥ. When the screen below appears, click on Next.ģ. Locate your download and double click it. If you aren't sure which Python version you want to install, choose Python 3. Go to the Anaconda Website and choose a Python 3.x graphical installer (A) or a Python 2.x graphical installer (B). With that, let's get started! Download and Install Anacondaġ. How to test your installation and fix common installation issues In fact, an installation of Anaconda is also the recommended way to install Jupyter Notebooks which you can learn more about here on the DataCamp community. 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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