Why Python is a leader in Data analysis and visualization Vs others

Todays world is undoubtedly ruled by data so why is python a leader in the data ecosystem? 

Let’s dive into it. 

Everyone has played with some form of data from spreadsheets to databases everywhere from work, school or online, data is in everything we do. Websites like Google, Wikipedia, Facebook all use data to show pages and run ads, images and layouts.  

Who can escape the world of data, quite honestly, no one, a simple click on a website is databased, your preferences on e-commerce sites, your hospital records, bank records, tax, everything is data kept as records in a database somewhere in private or public domains. 

Data is at its most basic, ones and zeros, but that’s at a computer level. The alphabets you type on a computer are ones and zeros but written as a human language you can understand. These human readable numbers and alphabets are what’s stored as data in most records be it a spreadsheet, an XML, JSON or CSV that’s later stored in actual databases like SQL, mongoDB, etc. 

Naturally most data needs to make sense, else it’s just a huge chuck of data that does say much till you actually apply some interpretation or a case study to it. 

Let’s take for instance a day to day recording of your goods or services. You may innocently just want to record what you buy as products and what you sell and maybe how much profit you make. A years worth of this record however can be used to show several patterns for you and your customers behaviors and when you apply an interpretation for predictions, you get a whole different outlook for that same data you collected. 

Some countries are tough on use of proprietary software, that’s why in some countries Microsoft office isn’t as popular because not many people can buy it for use. You then hear of other open source software like Libreoffice which can be gotten and installed on most kinds of computers to do what Microsoft office does, especially Microsoft Excel. 

Excel is a very intuitive spreadsheet manager, you can do way much more than spreadsheets in excel but it’s pretty high up for individuals and companies for keeping records. However, as mentioned earlier, excel comes with Microsoft office, so you have to pay for the whole suite, to be able to enjoy Excel. 

When installed Excel just runs pretty much fine with or without an internet connection and gives to awesome capabilities especially the table’s function. 

Other players like Google also have spreadsheets free to use and as powerful as excel, though an internet connection may be required. 

So how does Python come in? Well in order to understand Pythons role in data, you need to appreciate that most spreadsheet applications can do mathematical functions in them, addition, subtraction, multiplication, and other more advanced calculations. These functions become critical in data analysis which will also be important for data visualization.  

Python is open source, another critical factor that has seen its rise to fame and adoption asides being a mature programming language for other things asides data. Python is ubiquitous, used in many many applications in the data recording, databases, website building for front and backend, applications, automation, you get the drift. 

In order to stay relevant, data must evolve, thus, data must step up from mere spreadsheets to dashboards and continue to evolve to machine learning and other more advanced predictive modeling, so Python sits right there, as a language for data processing and automation to make that data come alive. 

I love Excel, but Excel’s time is passing, Microsoft with its PowerBI is trying it’s best to compete in the data ecosystem but there’s always something huge about the open source community you cant replicate, the share strength of numbers, number of programmers, projects, models, and more. These help the community build upon other people’s work, create unique projects, contribute libraries that can just be imported to be used by others, NumPy, MatPlotLib, Panda’s all examples of years of Python programming collaboration and modules free to use for data analysis, visualization and automation. Python programmers have had to interact with data from many many sources so there’s always a module to get to interact with a database that’s not python based but it’s surely out there, so you can stay Py-ing.

In essence, with whatever computer you have, PC, Linux, Unix, Mac, you can whip up a browser or terminal, install Python with or without an IDE and start doing amazing stuff with Python for free. The caveat however is that there is a bit of a learning curve to python since it’s so vast. You may also need an internet connection to import modules and libraries you don’t already have installed.

So the take homes are, Python is a very strong and mature open source programming language employed for its versatility with the data community as a data processing (frontend), data storage (backend), data visualization (with some of its libraries Plotly, MatPlotLib, Pandas) and automation/machine learning (Beautiful soup, tensorflow). As a free and open source tool, it’s definitely here to stay and it’s rise continues to soar in the ever changing world of data and the race to AI. 

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Written by Mundez
edmundez@me.com