Setting Up Python for Data Analysis

If you read my last article, I am sure you are excited to have come this far in this data analysis thing. We are going to look at what you require and how to actually go about installing python for data analysis. Python is a high-level programming language. This means that it enables a programmer to write programs that are more or less independent of any particular type of computer. It is a general-purpose language but I am going to tell you how to set it up for data analysis.

As usual, I will not want to bore you with anything that you will not need. However, if you do not remember any other thing about the python programming language, remember that it was created by Guido van Rossum. The design philosophy, like I already hinted at before is emphasis on code readability. With it you express concepts in fewer lines of code than would be possible in languages such as C++ or Java.

Learning about python, almost every tutorial I came across presumed I already had python setup to go. It was frustrating to learn the beginner tips on a browser or read it up without having a single idea how to actually start some coding of your own.

Housekeeping.

Python is opensource. This means that you do not need any license before or after installation to use it. The source code is open so developers and groups of developers have been able to supplement functionality for varying purposes. Because of this, there are so many applications that have python put together in such a way that all the necessary tools are packed into one place for some specific purposes. I will come back to this point in a minute.

Requirements

A computer that has internet connection is all you need to start. Initially at least, as you will have to download the initial setup files. I am going to guide you through downloading and setting up your MS Windows computer. This choice is informed by a predominance of Windows around us here in Nigeria at least. However, deployment is still very possible in other operating systems. Matter of fact, nowadays many Linux and UNIX distributions include a recent Python. Even some Windows computers (notably those from HP) now come with Python already installed. 

Installation

Navigate to the official python downloads and grab the latest stable vision. As I write, 3.7 is it. Choose between the two executable installers with x86-64 and x86 in their name for 64 and 32bit Windows respectively. If you are unsure of which you are running, head to your desktop, right-click on This PC, Computer or My Computer (depending on the Windows version you are running) and click on properties. Under System, find your System type.

Once your download finishes, open the downloaded file and follow the installation wizard: reading and accepting the terms as well as going with the default installation location suggested. If for any reason your anti-virus raises an alarm ignore or identify as a false positive. Installation is complete. Easy right? Hopefully this setup went smoothly; otherwise let me know.

Testing

We need to make sure everything installed correctly. To do this, open a command prompt by hitting the key on your keyboard that has the windows logo on it or clicking on the start button and typing cmd. Click on Command Prompt to open it. Type python and hit enter. You should see something like:

"Python 3.6.5 (v3.6.5:f59c0932b4, Mar 28 2018, 16:07:46) [MSC v.1900 32 bit (Intel)] on win32

Type "help", "copyright", "credits" or "license" for more information.

>>>"

You probably have 3.7. It doesn't matter. You are setup and good to go!

I earlier mentioned how developers have built suites of python packed with some extensive and cool features put together for use. With the installation you just did you can run any python script on your computer. You can also use it to follow along all the tutorials you learn as a beginner. You will notice one thing however: once you are done, you have no way of saving your work. Sucks right? Well, that's definitely not what we want. This is where the packages I talked about earlier come in handy.

One of my favorite text editors that provides a space that highlights python syntax as well as suggests and auto-completes codes on the go for you is atom. There are other interactive text editors out there too. Then, if you are going to do data analysis with python, you will have to get anaconda, the self acclaimed "Most Popular Python Data Science Platform". Get it here for Windows. If you are not able to get atom, anaconda will also provide you a text editor where you can write, run/execute and save your work.

I hope to tell you a few more things about these packages which will help you know and decide when to use which.