#Anaconda distribution for mac#
#Anaconda distribution mac os#

Also, choose the 64-bit installer if you have a 64-bit operating system, otherwise go with the 32-bit installer. Choose the Python 3.5 version, you can install Python 2 versions later. Instead, the default Python used by your scripts and programs will be the one that comes with Anaconda. You can find the installers and installation instructions at If you already have Python installed on your computer, this won’t break anything.

#Anaconda distribution mac os#

Installing Anaconda Anaconda is available for Windows, Mac OS X, and Linux.

#Anaconda distribution for mac#

Conda is a program we will be using exclusively from the command line, so if you aren’t comfortable using it, check out these learn by doing videos on command prompt tutorial for Windows and Linux Command Line Basics for Mac OSX/Linux

You can still install any of the available packages with conda, that comes by default with the standard version. Anaconda is a fairly large download (~500 MB) because it comes with the most common data science packages in Python, for people who are conservative about disk space, there is also Miniconda, a smaller distribution that includes only conda and Python. When you download Anaconda first time it comes with conda, Python, and over 150 scientific packages and their dependencies. We also use it to install, uninstall, and update packages in our project environments. We usually used conda to create environments for isolating our projects that use different versions of Python and/or different version of packages.

It comes with conda, a package, and environment manager. So, Why Anaconda? Anaconda is a distribution of packages built for data science. In most of the real world Data Science projects, conda based package and environments are widely used and I personally preferred conda based package installation and maintenance of project then installing and maintaining directly PIP based packages. Secondly, using conda to manage your packages and environments will reduce future issues dealing with the various libraries you’ll be using. Firstly, since Anaconda comes with a bunch of data science packages, you’ll be all set to start working with data. Listing, Sharing & Removing Environmentsįirst of All, What is Anaconda & Why Should I bother about it? You probably already have Python installed and will be wondering why you need this at all.What is Anaconda & Why Should I bother about it?.We will be covering most of these topics in following order: In this Article we will be installing Anaconda, managing python packages, creating individual conda environments and sharing them via conda YAML file.