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Why I Prefer Python as the Tool of Choice for Data Analysis in 2024
And why I recommend it to Aspiring Data Analysts (+ FREE Roadmap of Python for Data Analysis)
The Market is flooded with Data Analytics tools. Some of the popular ones out there are Tableau, SQL (Oracle, MySQL, Postgres), Sisense, SAS, Excel, Power BI, and the list is not even 1% done yet!
It is easy for aspiring Data Analysts to get completely lost in getting a hang of each and every tool. But from my experience, learning Python for Data Analysis is never a disadvantage. In fact, it might even set you apart from the rest of crowd. Here are my reasons why:
It is FREE
Python is a free, open course, general purpose programming language. So you do not need a subscription, or a one-time payment or any licence to start using it.
Although some of the above mentioned softwares have a free version, they have restricted features in the free version, and you will have to shell out money to get access to all the advance features as well.
Meanwhile Python is completely free to use, and so are most of the popular libraries that you would use for Data Analysis and Visualisation (and even dashboarding!!)
It is Platform Agnostic
Python is platform agnostic. It can be installed on Linux, Windows as well as Mac OS, unlike Power BI, whose Desktop version (full-feature version) is only available for Windows. They offer a web version which can be used on other platforms, but it comes with many feature limitations.
It is Easy to Learn
Python is the most recommended programming language for beginners with no coding background. The reason for this is that Python’s code structure is very easy to understand, therefore making it easy to debug. The commands are very straightforward and simple.
Since it has applications in almost every field involving code, people from any of these fields can easily learn and use Python in their work environment.
