LETS LEARN TECH TOGETHER (PYTHON PROGRAMMINGLANGUAGE) #02

Hello friends, welcome to my blog.
Last week, we got to know what programming means and how to become a good programmer.
This week i will be writing about one of the easiest and most popular programming language, The Python Programming Language. Although it may be new to some of you, but Python has been on the programming stage for over two decades.

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There are two main reasons you should learn Python. First, it has several technical advantages compared to other programming languages. And second, its practical application covers several industries. It is a powerful computational tool when we have to solve complicated tasks in the field of finance, econometrics, economics, data science, and machine learning. Therefore, it is a perfect stepping stone for somebody who learns how to code and is determined to pursue a career as a data scientist. Here's a slightly more technical description of Python. It is an open source, general purpose, high level, programming language. Let's break this definition into several pieces and try to understand each of these attributes.

1. Open-source means it is free. Python has a large and active scientific community with access to the software source code and contributes to its continuous development and upgrading. Depending on users' needs, this is the main reason Python is cross-platform. It is available for all major operating systems, Windows, Mac, and Linux. The benefit of it is Python can be quickly applied anywhere. Domain specific languages like MATLAB and SaaS also used for solving financial and econometric tasks are paid. This plays a role in a language's popularity.

2. General purpose. Yes, we will dig deeper in one of Python's specific applications, analysis of financial data. However, you should know there's a broad set of fields where it could be applied. For instance, Python can be used for web programming through the django framework. Although this is beyond the scope of this course, you should be aware of the wide scope of application and the interoperability with other programming languages could be an explanation why some large organizations have chosen Python as their main programming language.

3. High level. This is slightly more technical.Broadly speaking, computers can run programs written in low level languages only, also called machine languages. So a program written in a high level language must be first interpreted into a low level language before it can be executed. This process takes time. There is specialized software and applications that will do this interpretation for you. The advantages of using a high level language are huge. It is difficult to code and understand low level programming languages. They are too technical. High level languages employ syntax a lot closer to human logic, which makes the language easier to learn and implement. It allows the programmer to focus on the task at hand, instead of trying to figure out unreadable lines of code.

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To summarize the technical advantages
that make Python a powerful programming language, often preferred over other programming languages, we can say the following. It is free and constantly updated. It can be used in multiple domains. It does not require too much time to process calculations and has an intuitive syntax that allows for complex quantitative computations. What we've said so far demonstrates Python's enormous practical applicability. It is one of the most popular programming languages in several fields. One of them is the world of finance. Just consider, today banks and financial institutions spend more on technology than any other industry. Thousands of developers work in financial institutions to maintain existing software and build new programs. There is a growing demand for people who have solid knowledge about the world of finance and Python programming.

It is clear we are living in the era of big data. People in different disciplines, economics, finance, computer science, marketing, and many more can retrieve huge amounts of data. We can talk about big data when we have millions of observations. In such situations, the computational capabilities of traditional data processing applications like Microsoft Excel become insufficient. We need a more powerful tool to tackle big data in more or less the same way, regardless of the field application. Python is perfect for these situations as it gives us flexibility.

To conclude, Python's popularity lies on two main pillars. One is that it is an easy to learn programming language designed to be highly readable with a syntax, quite clear and intuitive. And the second reason is its user friendliness does not take away from its strength. Python can execute a variety of complex computations and is one of the most powerful programming languages preferred by specialists.

Thank you for reading, you can ask your questions in the comment box.