Discoveries and developments happen so often in the world of technology that it is no longer possible to mark all the success stories and accept them all. Some developments do leave a mark for certain reasons. Python is one such programming language that arrived in a market with a considerable number of successful peers and more in the making. But since the very beginning it has been making a mark. Whether or not this statement is clichéd I do not seem to know but I must say that it is very hard to be simple if you are a coding language and still harder if you are used for data science applications. Python achieved just this. Its very conception was focused on simplicity and agility, and it seems that the world actually needed these qualities.
The basics are easy to learn
Python is often recommended as the first programming language to learn. If you deduce from it that Python is a basic entry level language with very limited powers then your concept needs changing. The real point is that Python unlike most of its predecessors uses familiar characters for coding. The characters are simply easier to remember and hence to apply. Apart from that triggering the same function requires a lesser amount of Python code than Java, C or Pearl. Fewer amounts of code means less bugs and less time spent in debugging; this is one of the main reasons that Python is so dear to the programmers. While depending upon your ability and experience you can more or less use any language for any purpose, using Python for data science is probably the easiest choice for a newbie.
The ease in applying NLP with Python
If we want to assess the applicability of Python in real time problems then Natural Language Processing has to be mentioned. A unnervingly large portion of the accessible data comes in the form of unstructured text – mostly through chat bots, social networking sites and e-commerce websites. While reading a piece of text and understanding its significance seems pretty easy for anyone with knowledge of the respective language the case is totally different when it comes to dealing with gigabytes of unstructured data regularly it requires a system that can read and process textual data. Python proves to be an excellent tool for NLP programming. Since NLP is required in most marketing and service oriented enterprises Python also has become a favorite among them.
Wide range of applications
Python is used in a multivariate range of software systems and it also claims essentiality in different industries. E-commerce, social media, digital security and other digital industries as well as the global marketing sectors use Python for applied data science and analytics. Python comes with a great processing power and speed. Most importantly, being open source, Python is affordable for the startups and small scale enterprises that might not have the budget to integrate SAS. It provides both economic balance and superlative service. No wonder it is used by the sorts of IBM, NASA, Quora, YouTube, Dropbox etc.
The Python libraries make life infinitely easier for analysts and programmers. After you are done with Python data science course, the libraries are probably going to be your best friends. Some of the Python libraries deserve a special mention while there are others which are very useful depending on what you are up to. Requests library is one of the most used and most adored libraries. It makes the handling of web requests much easier. The Robobrowser library is rather new but has already made a mark for its effectiveness in simulating a browser. Scrapy is an excellent tool for data extracting. These tools being free and easily available, play a crucial part in Python’s coming up as a major language.
The Community of People
Since has been around for a while now the community of users has grown pretty strong. The language has impressed the young coders and they are eager to voice and to know about developments and unique usages of Python. Not only do you find solutions for numerous programming related problems from this community, these user forums also play a role in making the knowledge of new functionalities available to the mass. Python being an open source system itself makes good use of these forums as they work as kind of a large research team.
These are only a handful of the features that have earned Python a hefty fan base. Undergoing a Python data science course should help you explore more.