According to the official Anaconda website, “the open source Anaconda Distribution is the fastest and easiest way to do Python and R data science and machine learning on Linux, Windows and Mac OS X. It’s the industry standard for developing, testing and training on a single machine.”
Essentially, it’s a Python and R distribution that bundles up everything you need (for Python especially) in one handy package.
Mmmm, sounds good. I’ll have that.
Anaconda comes pre-loaded with the Python language and over 100 Python packages. You could have downloaded Python from it’s official home at Python.org but then you’d have only got the standard vanilla libraries/packages. Anaconda steps it up a level.
Installing new packages if you need them is simple and easy with the in-built package manager conda.
You also get the Spyder IDE (Integrated Development Environment) to edit your Python code in.
The main reason I advise installing Anaconda though is to also get the Jupyter server and Jupyter Notebook which come pre-packaged with Anaconda.
From Jupyter.org: “The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more”
It has quickly became the #1 way for data scientists using Python to distribute and share their code and projects to a wide user base.
Bonus points are given seeing as it’s incredibly easy to get started using it for absolute beginners.
You could have installed Python straight from Python.org as I said above. You could then go on and set up an IDE yourself or download and install Jupyter Notebook by itself.
As this is Simple Analytical however, I would rather keep things as simple as possible.
Anaconda is an extremely powerful, open source, fast, easy way to get started coding Python and using to start analysing data.
Let’s not look a gift horse in the mouth. Let’s just get it downloaded and installed.
1) Click on over to the Anaconda website and click on the big green Downloads button in the top right corner of your screen. Under the Download Anaconda Distribution banner you’ll see the latest available version number (5.3 in the example below) and the Release Date (September 28, 2018 below).
Under this you can see a “Download For:” with three icons – the four part rectangle for Windows, the Apple for Mac OS X and the Penguin for Linux. Click on the Windows icon.
Or alternatively just click this link to go straight to the Anaconda Windows download page.
2) Now we have a decision to make. You could either choose the Python 3.7 version and click Download or the Python 2.7 version and click the Download button over there. I suggest going with Python 3.7.
The debate rages on far and wide across the internet and the whys and wherefores are innumerable. Let’s not get caught up on all of that. Just Download the Python 3.7 version. End of story.
3) After clicking Download, I was shown this screen to enter my email address and get a free Anaconda cheat sheet. Always nice to get something for free so I took it. Never know when these things can come in handy. Choice is yours though.
4) The installer package download came in at around 650MB for me so depending on your download speed, you might have to wait for a few minutes. Click Run on the “Open File – Security Warning” pop up and go put the kettle on. Play Candy Crush on your phone. Do a handstand. Whatever. It’ll get down soon enough. When it does, locate your downloaded file (maybe in your Downloads folder) and double click it.
5) When you get to the Welcome To Anaconda Setup screen you have another decision to make. It’s going to be either: a) click Next and begin the next exciting phase of life with Anaconda/Python/Jupyter etc. in it or b) click Cancel and go do something else for the rest of your empty, unfulfilled life. Choice is yours. I clicked Next. Let’s see where it takes us.
6) Oh right, it’s just the License Agreement. Extra bonus points if you actually bother to read it. I’m sure it’s all above board and in order though so click on “I Agree” and keep this train a rollin’.
7) Next screen is the Select Installation Type. I go with the recommended option of “Just Me” here as I’m the only one using this particular Windows machine. If you are an admin on the PC and want it available for everyone who uses the computer in your office / school / library / prison block, select All Users instead and hit Next.
8) Make sure you are happy with the Destination Folder the installer has selected and either make a change or just click Next again.
9) Anaconda steps up the stakes on the next screen with some Advanced Installation Options. The dialogue is quite clear that they don’t recommend clicking the “Add Anaconda to my PATH” checkbox. If you have a burning desire to do this then I’ll either assume you know more about this than I do or are a reckless thrillseeker and adventurer. Either way, this isn’t really the place for you so I suggest leaving everything AS IS. Click Install, sit back and watch the green bar moving across the screen. This might take 5 or 10 minutes.
10) If all has went to plan you’ll now see this. Hurrah! Click Next.
11) You’ll now get the option of another free bonus from installing Anaconda, in this case the open source Microsoft code editor Visual Studio Code. I’m a sucker for a freebie as I said and have been rather interested in seeing what VSC can offer so I hit Install Microsoft VSCode. If you don’t want it then click Skip.
12) If you went for the VSCode installation, you’ll hopefully now be seeing this. Click Next. We’re almost there.
13) And there it is, the Thanks for Installing Anaconda notice. Job done. Celebration drinks are on me. Click Finish and we’ll call it a day.
So we’ve installed Anaconda. It went much the same as most other Windows application installations you might say. Because it did. But we’ve made major inroads into giving ourselves the tools necessary to begin our journey deeper into the world of data science and analytics. The real hard work is still to come of course but we’ll take it gently.
For now, we have somewhere to type and run our code and that – for today – is a victory.
Well done. See you next time for your first forays into doing something useful with Python, Anaconda and Jupyter Notebook.