If you are reading this blog then you must be looking for data science as a career option. And for that, you must have heard that you should learn python. But why python and not any other programming language. There are hundreds of programming languages in the market which can do the task for you. But why is everyone talking about python for data science? There are a number of reasons for that. It is open source. It is free and it is interpreted and not complied. This blog will take you through some of the points which can help you understand its usability. Also, we will be comparing python with other prominent programming languages and will see why is it the best in the market.
First, there are some intrinsic points which itself makes python best for the data industry. It is very simple to learn and use. Even a beginner can start using it within just a week of training. You can use it in almost all the industry. Though it has great applications in the data industry in web development world as well it has proved its importance.
Now, let us compare python with other programming languages so that you can see the differences by yourself.
Python vs. Java
Similar to python, java is simple and fast to work with. It has its own place in website development and app development. But there are differences as well. They both follow and allow object-oriented programming but java is more procedural and is more static. It means there is a high probability of getting a syntax error in java as compared to python. One major difference is how they both treat whitespaces. In python, the whitespaces are ignored but in java, it takes into account the number of whitespaces.
Python vs. C++
See, C++ is generally there in the field of web development because it is more suited to it. This does not mean that it cannot do data science tasks but python way ahead in it. C++ requires a .NET framework to work with but in python, you do not need any other frameworks. This language alone is sufficient to do anything in general. Most of the Microsoft products are based on C++ and many people use it for creating web pages and backend of many software. Again, python is faster than C++ and can do the same task in fewer lines than it.
Python vs. PHP
Here the distinction is very clear. PHP is only a scripting language and cannot be replaced with a full-fledged programming language. If you want to create the backend of a site or an application then PHP is best. But for a complete project cycle, you need a complete language as well and not just a scripting language. So there’s no comparison between two and python is way ahead in it. Also, PHP is not capable of handling a whole project on its own. You need to embed its code into some other language to do the desired task. It is generally there with HTML to make up the backend as stated before.
Python vs. Ruby
Here we have one similarity between python and ruby. Both languages are interpreted and not compiled. But again, for data science and scientific applications, python is far better than any other language. And the most important thing is that python is very simple and easy to learn. Even if in future a more data-friendly language comes but it has to beat python in terms of simplicity and usability then only it can be placed higher.
In the end, we see that no other programming language is even close to being compared with python. Only R language is closer in terms of its handling with data and scientific calculations. But when we talk about learning it then python takes the edge.
If you want to learn python for data science then you can reach PST Analytics for help. If you are looking for data science training then again you can give them a bell. PST is a data science institute based out in Delhi. You can check their website by clicking on the link above to know more about it.