Its download size is around 50MB or less than a tenth the size of Anaconda. The Miniconda distribution packages together just Python, conda, and a small number of other packages. The distribution also install conda, an important and necessary tool to manage packages and environments. Both of the programs aren’t necessary to do data science with Python. The distribution comes with a few other pieces of software such as Anaconda Navigator, a graphical user interface for those less comfortable with the command line, and qtconsole, a terminal-like program with the ability to make graphs inline. Most of these packages are unnecessary when first getting started. You can see the package list for each installation. The Anaconda distribution installs the latest stable version of Python along with over 200 packages. The current download size sits at around 600MB and will take up over 2GB of disk space once installed. My main criticism with the Anaconda distribution is the amount of excess software and Python packages that are installed onto your system. While installing the Anaconda distribution is a valid way to get started, I believe there is a better approach. Installing this distribution with the default settings should allow you to quickly get started doing data science work in Python.
Common Data Science SetupĬurrently, the standard advice for someone who desires to get their system set up to data science in Python is to download and install the Anaconda distribution provided by a company with the same name. Take my free Intro to Pandas course to begin your journey mastering data analysis with Python. You’ll have a single, robust environment which minimizes dependency issues by relying on the conda-forge channelīegin Mastering Data Science Now for Free!.Conda is installed to manage packages and environments.Python is installed with only the most common and useful packages for data science.By the end of the tutorial, your system will be set up such that: In this tutorial, I will describe a process for setting up a lean and robust Python data science environment on your system.
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